Large Language Models | Field

Lead research scientist at Ai2 and a founding member of the OLMo team. He works on open language models, language agents, evaluation, and reasoning, and helps build open-model research infrastructure.

AI researcher at DeepSeek working on natural language processing, code intelligence, and large language model reasoning.

Amanda Askell is a philosopher and AI alignment researcher at Anthropic. Her personal site says she previously worked as a research scientist on the policy team at OpenAI.

Senior Algorithm Expert in Alibaba Tongyi Lab's Language Technology Lab and Qwen Team member whose work focuses on multilingual large language models and machine translation.

Mona Jalal is a computer vision research engineer at Toyota Material Handling. Her homepage says she leads 3D computer vision work such as 6D object pose estimation and synthetic data generation, previously worked as an R&D engineer at UC Berkeley's FHL VIVE Center, completed doctoral study in computer vision at Boston University, and earlier earned master's degrees in computer sciences and electrical engineering from the University of Wisconsin-Madison.

Yuxiang Zheng is a Ph.D. student in electrical and computer engineering at Memorial University of Newfoundland. The homepage says Yuxiang Zheng received double B.Eng. degrees in electronics and electrical engineering from the University of Glasgow and the University of Electronic Science and Technology of China in 2021, an M.Sc. with distinction in communications and signal processing from Imperial College London in 2022, and studies reinforcement learning and quantum machine learning for 6G vehicular networks.

Ming-Yu Liu is a vice president of research at NVIDIA and an IEEE Fellow. He leads the Deep Imagination Research group, which focuses on deep generative models for content creation and foundation models for physical AI. He previously held research leadership roles at Mercedes-Benz Research and Development North America and National Tsing Hua University, and he earned degrees from National Taiwan University, National Chiao Tung University, and the University of Illinois Urbana-Champaign.

Xinyun Chen's homepage identifies her as an AI research scientist at Meta Superintelligence Labs, previously a staff research scientist at Google DeepMind. It also lists a PhD in Computer Science from UC Berkeley and a BS in Computer Science from Shanghai Jiao Tong University.

Xueyan Zou is an assistant professor in the College of AI at Tsinghua University. Her official Tsinghua page says she works on interactive embodied intelligence powered by world models, dexterous control and sensing, and embodied foundation models, after receiving a Ph.D. in computer science from the University of Wisconsin-Madison and then becoming a postdoctoral fellow at UC San Diego's Contextual Robotics Institute.

Arash Vahdat is a research director at NVIDIA Research, where he leads the GenAIR team on fundamental generative AI research. Before joining NVIDIA, he was a research scientist at D-Wave Systems and a research faculty member at Simon Fraser University, where he led video analysis research and taught machine learning for big data. He earned a PhD in computing science from Simon Fraser University.

Haoyu Lu is a Ph.D. student at Renmin University of China working on multimodal foundation models and video understanding. His homepage highlights papers and code including DeepSeek-VL, UniAdapter, and VDT.

Research Scientist at OpenAI focused on reasoning and agents. Previously at Google Brain, he worked on T5X, PaLM, Flan-PaLM, and Flan-T5, and he earned a PhD at MIT.

Dilek Hakkani-Tur is a Professor of Computer Science at the University of Illinois Urbana-Champaign and an Amazon Scholar at Amazon Health Science. Her UIUC faculty profile says her research interests include conversational AI, natural language and speech processing, spoken dialogue systems, and machine learning for language processing.

Jialong Tang works at Alibaba Tongyi in Hangzhou. The homepage says Jialong Tang received a Ph.D. from the Chinese Information Processing Laboratory at the Institute of Software, Chinese Academy of Sciences in 2023, a bachelor's degree from Xiamen University in 2018, and studies natural language processing, event understanding, multilingual systems, and Qwen large language models.

Research scientist at Tongyi Lab, Alibaba Group, working on multimodal large language models, machine reasoning, and efficient learning.

Alexandre Ramé is a research scientist at Google DeepMind and an adjunct professor at Ecole Polytechnique. His homepage says he previously held research roles at NYU and SCAI / Sorbonne Université, completed a PhD in machine learning at Ecole Polytechnique and ENS Paris-Saclay, and works on post-training and alignment for Gemma LLMs.

Benyou Wang is an assistant professor at the Chinese University of Hong Kong, Shenzhen. His official school profile lists academic areas in artificial intelligence, computer science, and speech and natural language processing, and his personal homepage says he leads the CUHKSZ LLM group after earning a Ph.D. in information engineering from the University of Padua plus earlier degrees from Tianjin University and Hubei University of Automotive Technology.

Brian Lester is a Senior Research Engineer at Google Brain and a PhD student at the University of Toronto advised by Colin Raffel. His public work focuses on efficient adaptation of large language models, including prompt tuning and related methods.

Kartikeya Mangalam is a PhD student in computer vision at UC Berkeley advised by Jitendra Malik. His public homepage says he previously held a visiting researcher role at Meta AI, studied in Stanford CS, graduated summa cum laude in electrical engineering with a machine learning minor from IIT Kanpur, and works on computer vision, video understanding, and human motion analysis.

Wanli Ouyang is a professor at Shanghai AI Laboratory. His homepage says he is also with MMlab and the SIGMA lab, obtained a PhD from the Chinese University of Hong Kong, and works on AI4Science, computer vision, and pattern recognition.

Researcher at OpenAI. He recently completed a PhD at UC Berkeley's BAIR lab, where he worked on machine learning for robotics, offline reinforcement learning, and self-supervised reinforcement learning.

Senior research scientist at the Allen Institute for Artificial Intelligence working on natural language processing, machine learning, and reasoning on the Aristo project; previously a researcher at the University of Stuttgart.

Computer scientist, UC Berkeley professor, and Databricks co-founder and CTO. He created Apache Spark and works on systems for large-scale data, machine learning, and compound AI applications.

Tulsee Doshi is a Senior Director of Product Management at Google DeepMind and currently leads product for Gemini Model. She previously served as Head of Product for Responsible AI at Google and holds both an M.S. and a Ph.D. in Symbolic Systems from Stanford.

Jason Phang is a researcher at OpenAI working on the Foundations team. His homepage highlights transfer learning and natural language understanding with large-scale language models.

Juntang Zhuang leads pretraining at xAI and previously worked at OpenAI. His homepage highlights Grok pretraining work and contributions to GPT-4o, GPT-4 Turbo long-context, DALL-E 3, and OpenAI embeddings.

Minhao Cheng is an assistant professor in the College of Information Sciences and Technology at Penn State. His homepage says he earned a PhD in computer science from UCLA under Cho-Jui Hsieh, served as an assistant professor at HKUST before joining Penn State in Spring 2024, and broadly studies machine learning with a focus on trustworthy machine learning and AutoML.

Researcher at OpenAI focused on data-centric methods for foundation models, including synthetic data and reinforcement learning. Previously a research scientist at Meta GenAI; earned BS, MS, and PhD degrees in computer science at Stanford.

Associate professor at Polytechnique Montreal, core academic member at Mila, and CIFAR AI Chair whose research spans continual learning, reasoning, meta-learning, and reinforcement learning.

AI researcher who co-created Sora at OpenAI and invented InstructPix2Pix during his PhD at Berkeley AI Research.

Tong Wu is a researcher at BIGAI in Beijing. His homepage says he works on diffusion language models, long context, and long sequence generation, and that he holds a master's from Tsinghua University and a bachelor's from Beijing Institute of Technology.

Utku Evci is a researcher at Google. His public Google Research profile describes work on making neural network training faster and more efficient, with public materials centered on sparsity, transfer learning, and machine intelligence.

Researcher and engineer working on artificial general intelligence; his public experience page lists him as a Member of Technical Staff at OpenAI, after roles at Google/X and Vicarious.

OpenAI researcher whose work spans alignment, machine learning, complexity science, open-ended evolution, and artificial life.

Member of Technical Staff at Anthropic working on reinforcement learning for LLMs; previously at Meta FAIR and the Kempner Institute at Harvard, with a Ph.D. from NYU and undergraduate study at Yale.

Junyang Lin (Justin Lin) is a researcher and open-source maintainer known for the Qwen family of models. His public profiles list interests in LLMs, AI agents, multimodal learning, long-horizon reasoning, world models, and reinforcement learning; multiple March 2026 news reports said he stepped down from the Qwen tech lead role.

Chinmay Hegde is an associate professor at the NYU Tandon School of Engineering. His public homepage and NYU faculty profile say he works on machine learning, optimization, and inverse problems, joined NYU in 2021 after three years at Iowa State University, previously completed a postdoc at Stanford University, and earned a PhD in electrical and computer engineering from Georgia Tech in 2016.

Scientist at OpenAI and president of the ML Collective research group, focused on understanding and controlling large neural networks. He completed a PhD at Cornell and previously helped start Uber AI and later founded Windscape AI.

Research leader at Google DeepMind working on language models, retrieval-augmented generation, post-training, and factuality. His homepage highlights foundational contributions including REALM, FLAN, and Gemini factuality work.

DeepMind researcher working on machine learning, computer vision, and structured learning from video and language.

Algorithm Engineer at the Qwen Team, Alibaba Group. He received his Ph.D. in computer science from Beihang University in 2024 and works on post-training alignment for Qwen models, with research interests in large language models, graph neural networks, and recommender systems.

Researcher at NVIDIA Research. Previously a PhD student in Computer Science and Engineering at HKUST, with earlier internships at International Digital Economy Academy and Microsoft Research.

Luke Zettlemoyer works on empirical methods for natural language semantics, machine learning, new tasks and datasets, and self-supervision for pre-training.

Engineer and product leader who worked on OpenAI's Applied AI team and now advises startups on AI products. He writes publicly about agents, retrieval, and evaluation on his personal site.

Research Principal at Meta Superintelligence Labs. He previously led the strategic explorations team at OpenAI and is known for foundational work on score-based diffusion models.

Researcher at Thinking Machines, formerly at OpenAI, working on real-time multimodal systems across language, vision, and voice.

Adria Garriga-Alonso is a research scientist at Google DeepMind focused on machine learning and AI safety. His public profile notes a PhD in computer science from the University of Cambridge in 2020.

Research scientist at OpenAI working on AI agents, large models, and reinforcement learning. Previously worked as an applied scientist at Uber and completed a PhD in computer science at ENS Paris-Saclay under Marc Schoenauer and Olivier Teytaud.

Claire Cui is a Google Fellow in the Google Brain team, where she leads research on deep generalist learning, large language models, multimodal learning, and interpretable AI. During her tenure at Google she helped found AdSense for Content and co-founded Google Health Research and Medical Brain; she holds a Ph.D. in computer science from Stanford and a B.S. in computer science from Tsinghua University.

PhD student at the University of Washington advised by Luke Zettlemoyer and researcher at Ai2. His work focuses on open language models, instruction tuning, data curation, and evaluation.

Postdoctoral researcher at the Allen Institute for AI and the University of Washington whose work focuses on open language model post-training, steerability, and evaluation.

TTIC and William Merrill's homepage describe him as currently at the Allen Institute for AI and incoming to TTIC in Fall 2026 after a PhD from New York University. Public profile pages describe research spanning transformer expressivity, formal language theory, computational linguistics, and language models.

Lester James V. Miranda previously worked as a Predoctoral Young Investigator at Ai2 and as a machine learning engineer on the spaCy team at ExplosionAI.

Public profiles say he completed a Georgia Tech PhD in 2025 after earlier study at Rice and USTC, and his current work focuses on bringing frontier AI to everyday devices.

Alibaba Qwen report author with public bibliography links for work on large language models, multimodal foundation models, and AI agents.

Xin Hu is a Member of Technical Staff at OpenAI focused on privacy and security. Xin previously held cybersecurity and machine learning roles at Robinhood, Pinterest, IBM Research, and Intel, and earned a PhD in Computer Science and Engineering from the University of Michigan.

Staff research scientist at Alibaba's Qwen Team and initiator of OpenDevin, focused on foundation models, reasoning models, coding agents, and computer-use agents.

Bowen Yu is an Algorithm Expert at Qwen (Alibaba Group) working on LLM post-training and automated alignment.

Sanjiv Kumar is a Google Fellow and vice president at Google Research. His public homepage says he leads teams working on large machine learning foundation models and generative AI, has spent more than 25 years building machine learning systems and products, and received a PhD in computer science from Carnegie Mellon University in 2005.

Shantanu Jain has worked on language models at OpenAI since 2020, focusing on training data and infrastructure. His homepage also highlights work in Python's open-source and static type-checking ecosystems.

Joshua (Josh) Achiam is Chief Futurist at OpenAI. He joined OpenAI in 2017 as a research scientist and has worked on AI safety research and operations, AI impacts research, and educational resources (including Spinning Up in Deep RL).

Research scientist at AI2; previously a machine learning engineer at Koko, where he worked on safety systems for language models.

Machine learning researcher focused on scalable learning and generative modeling, known for work on variational autoencoders, Adam, Glow, and variational diffusion models; his homepage says he is currently at Anthropic.

Research scientist at OpenAI working on intelligent agents, computer vision, natural language processing, and robotics; he previously completed a PhD in computer science at Penn State.

Researcher working on machine learning systems and infrastructure at OpenAI. He earned his PhD from UCLA.

Ming Lin is a professor of computer science at the University of Maryland, College Park and the chief executive officer and co-founder of Aitrios.ai. Her public homepage says she was the founding director of the GAMMA lab, previously served as assistant dean of the University of Maryland's Institute for Advanced Computer Studies, and earned her BS, MS, and PhD in EECS from the University of California, Berkeley.

Research scientist at Meta AI working on natural language processing and AI safety. His homepage says he completed a PhD at Facebook AI Research and Inria focused on text simplification and accessibility.

Research scientist at Meta GenAI working on efficient and safe language and multimodal systems. She completed a Ph.D. in computer science at Carnegie Mellon University.

Hannaneh Hajishirzi is Senior Director at Ai2 and a professor of computer science at the University of Washington. Her public materials focus on generative AI, reasoning, open language models, pre-training, and evaluation.

Junxian He is an assistant professor in computer science and engineering at the Hong Kong University of Science and Technology. His public homepage and Princeton profile say he works at the intersection of natural language processing and machine learning, focusing on scalable methods for language model training and reasoning, completed a PhD in computer science at Princeton University in 2024, and previously earned bachelor's degrees in economics and computer science from Peking University.

Tyler Murray is a research scientist on Ai2's PRIOR team working on vision and multimodal models. His OpenReview profile shows previous research engineering roles at Google and Facebook and degrees from Stanford University and the University of California, Berkeley.

Yukun Zha is a research scientist at DeepSeek. His public profile lists research interests in machine learning, reinforcement learning, and efficient inference, alongside a PhD in computer science from Dartmouth College.

Research scientist at Google DeepMind working on Gemini. He previously worked at Meta, OpenAI, and Google Brain, and earned a PhD from UMass Amherst.

Research scientist at Meta FAIR focused on computer vision and multimodal understanding, including image and video models, visual reasoning, large-scale training, and evaluation.

The Allen School lists Pang Wei Koh as an assistant professor at the University of Washington and a visiting research scientist at the Allen Institute for AI. The same page lists expertise in explainable AI, generative AI, machine learning, and natural language processing.

Daogao Liu's homepage says he is currently a visiting postdoctoral researcher at Google. It says his research focuses on machine learning and theoretical computer science, especially differential privacy, stochastic optimization, and algorithm design.

Rulin Shao's homepage says he is a third-year PhD at the University of Washington advised by Pang Wei Koh and Luke Zettlemoyer, and also a visiting researcher at Meta.

NVIDIA Research and Wonmin Byeon's personal site identify him as a researcher at NVIDIA Research in California. Public site materials describe interests in computer vision, robotics, recurrent and state-space models, sequence learning, and spatio-temporal learning.

Co-founder and CEO of Ideogram whose public homepage highlights work on self-supervised representation learning, generative modeling, and multimodal learning; previously a senior staff research scientist at Google Brain Toronto.

Research scientist at NVIDIA working on compression, efficient inference, post-training, multimodality, and evaluation for large language models. He completed a PhD in machine learning at Stanford and a master's in artificial intelligence at the University of Edinburgh.

Hao Yang works on multimodal data infrastructure at Moonshot.ai. He previously worked at ByteDance ICVG and Microsoft Research Asia, and received BS and PhD degrees from Tsinghua University.

Research scientist at OpenAI whose public profiles highlight multi-agent alignment, scalable training, and reinforcement learning.

Leon Derczynski is a professor in natural language processing at DTU Compute whose research focuses on information extraction, online harms, and the dynamics of abusive language and misinformation.

Jin Xu's homepage says he leads the audio group at Qwen Team, Alibaba, working on audio understanding, real-time multimodal interaction, speech synthesis, general audio synthesis, and audio-centered chat models. He previously completed a Ph.D. at IIIS, Tsinghua University and received a BSc in 2018 from Beijing University of Posts and Telecommunications.

Noah A. Smith is the University of Washington's inaugural Vice Provost for Artificial Intelligence and a professor in the Paul G. Allen School of Computer Science & Engineering. He is also Senior Director of NLP Research at the Allen Institute for AI.

AI researcher and former OpenAI scientist who became chief scientist of Meta Superintelligence Labs in July 2025; public academic sources also show earlier Stanford and Tsinghua training.

NVIDIA's research page describes Jan Kautz as vice president of Learning and Perception Research, working across computer vision, machine learning, computational photography, and geometric vision.

Valentina Pyatkin works on open language models, post-training, steerability, instruction following, and evaluation as a postdoctoral researcher and Young Investigator at Ai2 and the University of Washington.

Yufei Guo is an assistant professor in the UCLA Computer Science Department. His public profiles note prior work as a research scientist at OpenAI and research interests in AI agents, reinforcement learning, and large language models.

Works on large language model interpretability at Anthropic; previously worked on scaling laws at OpenAI and ML engineering at Beehive AI, and completed a Ph.D. in physics at Stanford.

Head of AI at Cohere and professor at the University of Pennsylvania whose public profiles focus on natural language understanding, reasoning, and grounding.

David Dohan is a computer scientist at OpenAI studying scalable alignment of language models and generally intelligent reasoning systems. His personal site also notes prior work at Google Brain on foundation model programs, code generation, protein engineering, and scientific reasoning.

Research scientist at Google DeepMind working on trustworthy deep learning, multimodal modeling, and generalization in AI systems.

Ahmad Al-Dahle joined Airbnb as Chief Technology Officer on January 14, 2026. Airbnb's announcement says he previously led Generative AI at Meta, founded Meta's Generative AI group in early 2023, and earlier studied engineering at the University of Waterloo and held senior technical leadership roles at Apple.

Hyung Won Chung is a Research Scientist at OpenAI working on reasoning and agents. His public site says he previously worked at Google Brain and completed his PhD at MIT.

Mitesh M. Khapra is a professor at IIT Madras and co-founder of AI4Bharat whose research spans natural language processing, machine learning, transfer learning, and deep learning.

Yu Wu's public homepage says he is a technical staff member at DeepSeek AI who leads the LLM Alignment Team and works on writing, QA, AI search, reasoning, and safety.

Trung H. Bui is a staff researcher at Cohere working on generative AI, large language models, natural language processing, machine learning, and computer vision.

Alec Radford is a researcher and a co-author of the GPT-4 Technical Report. His GitHub profile links to his personal website at newmu.github.io.

Seungyoun Hong is a research scientist and postdoctoral scholar at Stanford University working on machine unlearning, data attribution, hallucination, and generalization.

Chuanqi Tan's homepage says he received a PhD from Tsinghua University in July 2019, is currently focused on LLM research and applications, and is also a postdoctoral fellow at the University of Hong Kong.

Vahid Noroozi is an applied research scientist at NVIDIA. His NVIDIA author profile says his work focuses on deep learning for speech and natural language processing and that he received a PhD in computer science from the University of Illinois Chicago. His homepage says he previously worked on post-training large language models at Google DeepMind after earlier multimedia and neuroscience research at TU Delft and the Max Planck Institute for Biological Cybernetics.

Jan Leike is a machine learning and alignment researcher who leads the Alignment Science team at Anthropic. He previously co-led the Superalignment team at OpenAI and earlier worked on alignment research at DeepMind.

Shuyue Stella Li is a Ph.D. student in the Allen School at the University of Washington advised by Yulia Tsvetkov, with research interests including proactive learning, social reasoning, and AI for health.

Member of the Technical Staff at Google DeepMind; his homepage says he previously led developer relations at OpenAI from 2022 through early 2024 and earlier worked at NASA and Apple.

Pengcheng Yin is a research scientist at Google DeepMind working on Gemini Code and natural-language-to-code generation. His homepage also lists earlier experience as a part-time research collaborator at Facebook AI Research and research internships at Microsoft research groups.

Researcher at DeepSeek whose public homepage describes work on DeepSeek R1, V1, V2, V3, Math, Coder, and mixture-of-experts systems.

Yizhong Wang is a research scientist at the Allen Institute for AI and incoming assistant professor at the University of Washington whose work focuses on language models, agents, reasoning, and open-source AI.

Vasu Singhal is an AI researcher focused on natural language processing, generative AI, and machine learning. He studied computer science at Stanford University and has worked on NLP research at FAIR.

Chris Alberti's Google Research profile lists natural language processing and speech processing as his research areas, and his OpenReview profile lists him as a researcher at Google.

Co-founder and CTO at Thinking Machines. Previously VP of Research (Post-Training) at OpenAI, Staff Research Scientist at Google Brain, and a researcher at the Information Sciences Institute.

Amjad Almahairi is a researcher at Anyscale. His OpenReview profile lists work spanning LLMs, VLLMs, generative models, and deep learning, with earlier roles at Facebook and Element AI.

Prasanna Parthasarathi is a research scientist at Huawei Noah's Ark Lab in Montreal. His public speaker and lab-profile pages say he collaborates with Mila and McGill University, works on natural language processing, dialogue systems, and social simulation, and completed a PhD at McGill University in 2022 under Joelle Pineau.

Sebastian Gehrmann leads Responsible AI in the office of the CTO at Bloomberg and works on natural language generation, model evaluation, and interpretability.

Can Cao is a Ph.D. student at Tsinghua University advised by Ming Zhou and Yuxuan Wang. The homepage says Can Cao received a bachelor's degree from Tsinghua University in 2022, previously interned at Microsoft Research Asia in summer 2022 and Meta AI in summer 2025, and studies large language models with a focus on pre-training, reasoning, agents, post-training, and multimodal learning.

Staff Research Scientist at Google DeepMind. Public Google profiles describe earlier work at Google Brain and Microsoft Research and research spanning machine learning, graph mining, and unstructured data analytics.

Hanrong Ye is a research scientist at NVIDIA Research in Santa Clara working on multi-task, multi-media, and multimodality models for machine understanding and generation. He earned a Ph.D. from HKUST, a master's degree from Peking University, and a B.S. from Sun Yat-sen University.

Public profiles identify Matt Jordan as an Allen Institute for Artificial Intelligence researcher and a former University of Texas at Austin PhD student advised by Alex Dimakis.

Shashank Gupta's public homepage describes him as an applied scientist at Ai2 focused on agentic LLMs, test-time compute, post-training, and reasoning, after earlier work in Microsoft AI.

Assistant Professor in Penn CIS, a primary GRASP faculty member, and a member of the ASSET Center; he also works part-time as a Staff Research Scientist at Apple MLR on multimodal generative models, reasoning, and embodied AI.

Research scientist at Cohere Labs and PhD candidate at Stanford University focused on language models, machine learning systems, and AI safety.

Jiahui Yu is a Research Lead at OpenAI leading the Perception team. His homepage notes prior co-leadership on Gemini Multimodal at Google DeepMind and work on deep learning and high-performance computing.

Ching-Yao Chuang is a researcher at OpenAI working on multimodal and generative AI systems. His homepage lists prior roles at xAI and Meta GenAI and a PhD from MIT.

Northwestern PhD student working on agentic RL, previously interned at DeepSeek, Microsoft, and Yutori.

Research scientist on the AllenNLP team at the Allen Institute for AI, where his homepage highlights work on open language models such as OLMo and Tulu and a focus on post-training language models.

Senior algorithm expert at Alibaba Group working on large language models, multimodal large language models, and diffusion models.

OpenAI's GPT-4 contributions page credits Ben Wang as attention architecture lead for long context. Public profiles identify him as a University of Pennsylvania undergraduate and an OpenAI researcher from 2021 to 2022.

Public profiles describe Wenchao Zhou as Director of Data Product and Data Analytics at Alibaba Cloud Intelligence and a former tenured computer science faculty member at Georgetown University. His work centers on databases and distributed systems.

Costa Huang is a reinforcement learning researcher and the creator of CleanRL; his public GitHub profile lists Periodic Labs as his current affiliation and AllenAI and Hugging Face as previous affiliations.

Jan Hendrik Kirchner is a researcher at Anthropic. His public OpenReview profile lists prior research work at OpenAI and a Brain Science PhD track through Max Planck Schools.

Carnegie Mellon says Maarten Sap is an assistant professor in the Language Technologies Institute with a courtesy appointment in HCII, and also a part-time research scientist and AI safety lead at the Allen Institute for AI. His CMU profile says he received his PhD from the University of Washington.

Matt Jordan is a researcher at Ai2 focused on making language models safe and reliable. His public profile says he previously spent more than four years at Google and is currently a PhD student in computer science at the University of Texas at Austin.

Jiatao Gu is an assistant professor in the University of Pennsylvania Department of CIS and a primary faculty member of GRASP Lab and the ASSET Center. His homepage also states that he works part-time as a staff research scientist at Apple ML Research after earlier work at Meta AI.

Shannon Zejiang Shen is a PhD student at MIT CSAIL researching collaborative AI systems that augment human intelligence.

William Merrill is a Young Investigator at the Allen Institute for AI and an incoming assistant professor at TTIC. His public faculty profile describes research on the computational power and limits of transformers, computational linguistics, and deep learning theory.

Yuling Gu's NYU and personal pages describe her as a PhD student at NYU Center for Data Science who previously worked at Ai2 and has contributed to OLMo and OLMES.

Research scientist at Google DeepMind interested in efficient and reliable language models, reasoning, and model security. His personal site also highlights prior work on planning, geometry, and representation learning.

Boris Ginsburg is a principal engineer and research scientist at NVIDIA whose work focuses on efficient machine learning and deep learning for speech recognition, language processing, and computer vision.

His GitHub profile says he works on robust and aligned AI at Anthropic and previously worked at OpenAI and Google Brain. He is the first author of the GPT-3 paper 'Language Models are Few-Shot Learners'.

Amelie Haghighat is an incoming assistant professor at the University of Illinois Chicago whose research focuses on trustworthy and resource-efficient machine learning systems.

Ana Klimovic is an assistant professor of computer science at ETH Zurich whose research focuses on machine learning systems, efficient hardware acceleration, and sustainable AI.

Compiler researcher and entrepreneur, creator of the PolyMage DSL, and Professor at the Indian Institute of Science whose work spans compilers, AI systems, and programming languages.

Rogerio Feris is a principal scientist and manager at the MIT-IBM Watson AI Lab within IBM Research. His public bios emphasize multimodal perception, data and model efficiency, and large language models with memory.

Jacob Morrison's homepage says he is a PhD student at UW and a student researcher on the AllenNLP team at Ai2, where he mainly works on language modeling.

Jiacheng Liu is a researcher at Ai2 whose work focuses on improving the capabilities and understanding of language models. His public homepage says he is currently a PhD student at New York University and has previously spent time at Princeton and Google Research.

Mayee Chen's public pages describe her as a Stanford computer science Ph.D. student and an AI2 research intern working on data-centric machine learning and natural language processing.

OpenReview identifies Yashaswi Karnati as a researcher at NVIDIA. His personal homepage describes prior work across intelligent transportation, climate science, data compression, and healthcare, and records completed degrees from the University of Florida and IIT (ISM) Dhanbad.

Founding AI Lead at Samaya AI with research interests in reasoning, retrieval, agentic systems, and reinforcement learning; previously completed a Stanford PhD in computer science under Christopher Manning.

Jingren Zhou is Chief Technology Officer of Alibaba Cloud. Public speaker biographies describe him as a computer scientist and entrepreneur whose work includes large-scale AI and cloud systems.

Jian Yang is an Associate Professor at Beihang University whose research focuses on code intelligence, large language models, and AI agents. He worked with Alibaba Qwen from 2023 to July 2025.

Aston Zhang is a member of technical staff at OpenAI, author of Dive into Deep Learning, and a core contributor to Llama 3. His homepage says he earned his Ph.D. from the University of Illinois Urbana-Champaign.

Thomas B. Brown is a research scientist at Google DeepMind whose work focuses on language models, multimodality, and reasoning.

Boris Ivanovic is a postdoctoral scholar in Stanford's Autonomous Systems Lab whose research focuses on human-centered machine learning and data-driven prediction and planning for autonomous systems.

Geri Skenderi is a research scientist at Cohere focusing on multilingual language technology, evaluation of large language models, and natural language processing for low-resource settings.

Hanlin Tang is a researcher at Cohere. His public page says his work focuses on foundation models, large language model post-training, reinforcement learning, and vision-language or language-model agents, and that he previously held research internships at NVIDIA and the Vector Institute.

Saumya Malik is a predoctoral young investigator at the Allen Institute for Artificial Intelligence working on open language modeling, reward models, and instruction following.

Yifei Qu is a technical staff member at JD Explore Academy in Beijing and a Ph.D. student at the University of Texas at Austin. The homepage says Yifei Qu received a master's degree from Carnegie Mellon University in 2023, a bachelor's degree from Sun Yat-sen University in 2021, expects to graduate in 2027, and works on learning and optimization, reinforcement learning, reasoning, and alignment for large language models under Peter Stone.

Yutao Sun is a fifth-year Ph.D. student at Zhejiang University supervised by Minlie Huang. The homepage says Yutao Sun has been a visiting student researcher at Stanford University since September 2023 under Tatsunori Hashimoto, earned a bachelor's degree from Tsinghua University in 2019, and studies code generation, code agents, execution feedback, and reasoning in large language models.

Public bios identify Arka Dhar as Product Management Director at Google DeepMind and former Head of Data at OpenAI. OpenAI contribution pages list him among contributors to GPT-4o-era model work.

Michael Noukhovitch is a PhD candidate in artificial intelligence at Mila associated with Universite de Montreal. His public homepage lists interests including reinforcement learning, multi-agent systems, natural language processing, and agents with web and computer use.

Research scientist at Meta AI working on natural language processing, dialogue systems, and large language models.

Algorithm expert at Alibaba DAMO Academy focused on natural language generation and large language models.

Researcher at DeepSeek AI working on decision-making and post-training for large language models.

Research scientist working on large language models and retrieval-augmented generation; creator of the open-source project tiny-universe.

Professor at the University of Washington and Senior Director of NLP at AI2. Her work spans natural language processing, computer vision, responsible AI, and applications to science and medicine.

Research scientist at DeepSeek interested in large language models, reinforcement learning, robot learning, and machine learning.

Yuling Gu is a PhD student at the NYU Center for Data Science studying large language models, machine reasoning, and robust evaluation. She was previously a predoctoral researcher at the Allen Institute for AI, where she contributed to OLMo, OLMo 2, OLMo 3, TULU 3, OLMoE, and OLMES.

Aakanksha Chowdhery is a machine learning researcher based in New York City. She works on large-scale machine learning across pre-training, post-training, inference, and system efficiency, and is known for contributions such as PaLM, Pathways, and Gemini.

PhD student at The Hong Kong University of Science and Technology (Guangzhou) whose research interests include large language models, vision-language models, AI agents, and multimodal retrieval.

Liyue Zhang is a research scientist at DeepSeek whose public profiles highlight multimodal models, reasoning, and AI agents.

Researcher at DeepSeek AI focusing on multimodal large language models and multimodal understanding.

Research scientist at DeepSeek AI. Previously completed a PhD at Carnegie Mellon University.

Steven Adler is a former OpenAI safety researcher and technical program manager (2020-2024). He writes Clear-Eyed AI, analyzing AI news, policy, and research with a focus on risk reduction.

Luca Soldaini is a lead research scientist at Ai2 on the Olmo team. He previously worked at Amazon Alexa and completed a PhD in computer science at Georgetown University in 2018.

Wangding Zeng is a researcher at DeepSeek. His OpenReview profile also lists graduate and undergraduate study at Beijing University of Posts and Telecommunications.

Jesse Dodge is a research scientist at Meta Superintelligence Labs. His public work spans evaluation, reproducibility, efficiency, and open large language models, and his homepage says he was at the Allen Institute for AI from 2019 to 2025.

Siyuan Li is a research scientist at NVIDIA working on large language models, multimodal foundation models, and reinforcement learning. His homepage says he received a PhD in computer science from the University of Toronto in 2024 and previously worked at Meta AI, Microsoft Research, and Mila.

Anej Svete is a PhD Fellow at the ETH AI Center. His homepage says he studies language models with formal language theory and completed a 9-month research internship at Ai2 in 2025.

Carlos Riquelme's public website describes him as a senior research scientist at Google Brain who previously completed a PhD in statistical machine learning at Stanford. His public materials emphasize machine intelligence, efficient and sparse models, and reinforcement learning.

Research Fellow at OpenAI focused on fundamental research on reasoning in neural networks. Previously completed a PhD in machine learning through the Center for Learning Systems at ETH Zurich and the Max Planck Institute for Intelligent Systems.

Stanford Data Science lists Jiacheng Liu as a PhD candidate in the Paul G. Allen School of Computer Science and Engineering at the University of Washington. Public sources also link this profile to OLMo 3 authorship and a past Allen Institute for Artificial Intelligence internship.

Shizhe Diao develops methods to scale post-training and reinforcement learning for large language models and AI agents.

Public sources reviewed support Biao Zhang as a researcher at Google DeepMind whose recent work covers multilingual machine translation, speech translation, and fine-tuning methods for large language models.

Matthijs Van keirsbilck is a Senior Research Scientist at NVIDIA working on neural network architecture design, structural sparsity, quantization, and training dynamics.

OpenReview lists Shane Arora as a researcher at the Allen Institute for Artificial Intelligence from 2023 to 2025, an MS student at UT Austin from 2021 to 2024, and an undergraduate student at the University of Sydney from 2016 to 2019. Ai2's public directory and papers pages also list Shane Arora.

Tim Green is a staff research scientist on Google's ML Foundations team. His homepage says he leads research at the interface of compression and memory to unlock more efficient language models, with interests spanning compression, memorization, and efficient model architectures. The same page says he previously completed a PhD in neuroscience at Stanford and a bachelor's degree in computer science and mathematics at Vanderbilt.

Researcher at Google DeepMind working on multilingual machine translation, speech-to-text translation, and efficient neural machine translation.

Research scientist at NVIDIA and University of Maryland PhD student whose public site highlights speech, audio, and video generation plus alignment for large language and vision-language models.

Research scientist at Google Research in New York City. He earned a PhD in computer science from NYU Tandon and works on language models, multimodal learning, NLP, and deep learning.

Co-founder and Head of Policy at Anthropic. His public biography also notes earlier work as Policy Director at OpenAI, a technical journalist, and author of the Import AI newsletter.

Research scientist at Ai2 and PhD candidate at the University of Washington. Her work focuses on language models, evaluation, and building practical open-source AI systems.

Ameet Talwalkar is an associate professor in the Machine Learning Department at Carnegie Mellon University and Chief Scientist at Datadog. His public research spans AI for science, human-AI interaction, and specialized models and agents.

Ph.D. candidate at the University of Science and Technology of China whose research focuses on improving the general reasoning abilities of foundational large language models, LLMs for recommendation, and scaling reinforcement reasoning; he lists himself as a core contributor to the Qwen2.5 and Qwen3 technical reports.

Mujeen Sung is an assistant professor at Kyung Hee University and formerly served as a technical lead at LG AI Research. His research focuses on natural language processing, controllable and efficient large language models, and language generation and interpretation.

Researcher at DeepSeek focused on large language models, reinforcement learning, multimodal large language models, and generative AI.

Research leader at Google DeepMind and Google Research focused on natural language processing and machine learning, including large language models such as PaLM and Gemini.

Yuntian Deng is a machine learning researcher whose public work spans language modeling, reasoning, and large multimodal systems.

Senior Research Manager and Senior Director at Tongyi Lab, Alibaba Group, leading agents and AI infrastructure research.

Chunlin Li is a research scientist at MiniMax.

AI researcher focused on evaluating language models and agents, open NLP research, and historical linguistics. She led evaluation efforts at Hugging Face between 2023 and 2025 and helped build LightEval and the Open LLM Leaderboard.

Ai2 engineer whose public GitHub and Hugging Face profiles describe him as building LLMs at Ai2; he is also listed on OpenReview as an OLMo author.

Research scientist at the UK AI Security Institute and former OpenAI member of technical staff who worked on model behavior and post-training research. Previously conducted computational neuroscience research at UC Berkeley.

Research scientist at Ai2 focused on language models, evaluation, and AI safety. Her work studies reasoning, truthfulness, and how to make large models more reliable.

OpenAI engineer focused on GPU systems and large-model infrastructure, with public contributions to GPT-4 and earlier OpenAI research on efficient GPU kernels and code models.

Research Scientist on the Qwen team at Alibaba Cloud.

Stanislas Polu is Co-Founder and Engineer at Dust. His public site also documents earlier work at OpenAI, Stripe, and projects in theorem proving, browsers, and Bitcoin-related systems.

Recent public bios describe Angela Fan as a researcher at Meta working on large language models, machine translation, multilingual generation, and story generation.

DeepSeek engineer and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Sandhini Agarwal is a researcher at OpenAI. Her OpenReview profile lists her as a researcher at OpenAI (2020–present) and an undergraduate student at Stanford University (2015–2019).

Shane Arora is a research scientist at Ai2. His The Org profile identifies that current role, and his OpenReview profile records earlier work as a senior applied scientist at Amazon as well as bachelor's and master's degrees in computer science from the University of Texas at Austin.

Allyson Ettinger is a senior research scientist at Ai2 working on the OLMo pre-training team. Her public materials focus on natural language understanding, language model behavior, and learning from text and experience.

Finbarr Timbers is an AI researcher and investor. His homepage says he works at Ai2 on RL for LLMs and previously worked at Midjourney and DeepMind.

Nathan Lambert's homepage says he is the post-training lead at Ai2, where he works on open language models and responsible autonomous systems. His public CV lists a PhD in Computer Science from UC Berkeley.

Dan Busbridge's public OpenReview profile lists him as a researcher at Apple, and his Hugging Face profile highlights interests including deep learning, optimization, and large language modeling.

Joshua Clymer works on AI safety and theoretical questions around superposition and representation learning. Current public mentor material places him at Redwood Research and previously at METR.

Senior Director, AI and Machine Learning Research at Apple and adjunct professor at EPFL. His homepage highlights work on reasoning limits for autoregressive models, deep sequence architectures, and ML systems.

Victoria Graf studies at the University of Washington and is publicly credited on open-model work including Tulu 3 and OLMo 3.

Assistant Professor of Computer Science at Johns Hopkins University working on helpful, reliable, and efficient language-driven AI systems. Previously a postdoctoral researcher at the Allen Institute for AI.

Samyam Rajbhandari is a principal AI research scientist at Snowflake AI Research. His public profile describes work on large-scale deep learning systems, distributed training, and efficient optimization, and lists prior Microsoft research experience.

Saurabh Shah's public site says he works at humans& and previously worked on post-training the OLMo language model at Ai2.

Scott Wen-tau Yih is a research scientist at Meta FAIR whose recent work focuses on neural retrieval and retrieval-augmented generation; his homepage lists prior roles at Ai2 and Microsoft Research.

Assistant professor at the University of Oxford and research scientist at NVIDIA. His public work focuses on robot learning, robotics, reinforcement learning, computer vision, and multimodal models.

Furu Wei is a Distinguished Scientist and Chief Scientist of Microsoft Research Asia, listed on Microsoft Research and connected in LLMpeople to Microsoft technical reports including Kosmos, VALL-E, BitNet, and Multilingual E5.

Founder and AI Advisor at Metaculus and a named contributor to OpenAI's GPT-4 Technical Report.

Chengyuan Li is a research intern with Alibaba's Qwen team. His homepage highlights work on reasoning and post-training for large language models.

R. X. Xu is a research scientist at DeepSeek AI. His homepage says he works on trustworthy and efficient large language models, open-ended reasoning, and AI for healthcare.

Shengding Hu is a researcher at Shanghai AI Laboratory and a PhD candidate at Tsinghua University working on large language models, multimodal models, and AI agents.

Research scientist at OpenAI focused on neural scaling, autonomous learning systems, language models, and reinforcement learning.

Software engineer focused on developer tools, infrastructure, and AI products. He has worked at OpenAI in San Francisco and publishes engineering projects and writing on his website and GitHub.

MPhil student in the Department of Computer Science and Engineering at HKUST interested in LLM agents and multimodal models; previously interned with the DeepSeek LLM Alignment Team.

Designer focused on brands, websites, and creative tools. He helped grow design at OpenAI from 0 to 1 and later joined Cursor.

Madelaine Boyd is a staff engineer at OpenAI. Her public GitHub profile links to her personal website, and official OpenAI contributions pages list her work on GPT-4 and GPT-4.5.

Michelle Pokrass is an OpenAI researcher working on multimodal AI, especially speech and audio. Her public profiles also show work on ChatGPT and model releases including GPT-4.1.

Researcher at DeepSeek focused on multimodal large language models, world models, reinforcement learning, and embodied AI.

Research scientist at Cohere focused on scaling machine learning systems and improving training efficiency.

Ph.D. student in Computer Science at Stanford University who previously worked on LLMs and agents with Alibaba's Qwen team.

Alejandro Lopez-Lira is an assistant professor of finance at the University of Florida whose research interests include investments, machine learning, and empirical asset pricing.

Alethea Power is a research scientist at OpenAI. Her personal website notes earlier PhD work at Georgia Tech and research interests spanning language, reasoning, cognitive science, and brain-inspired approaches to intelligence.

Andrew Cann is a software engineer at OpenAI. His public website and GitHub profile identify him as an OpenAI engineer, and OpenAI's contributions pages list his work on GPT-4 and GPT-4.5.

Benfeng Xu is an LLM post-training researcher at Alibaba Group and an incoming assistant professor at Carnegie Mellon University. His homepage says he works on language models, efficient and trustworthy machine learning, AI for science, and biomedicine.

Researcher working on language models, agents, and retrieval-augmented generation; currently at xAI and incoming assistant professor at the University of Washington, previously a research scientist at the Allen Institute for AI.

Applied scientist at Amazon focused on natural language and speech processing, machine learning, and multimodal learning.

Research scientist at DeepSeek interested in reinforcement learning, large language models, and reasoning.

Researcher at Alibaba's Qwen team, previously a PhD student in the CUHK Text Mining Group, working on RL for LLM reasoning and alignment.

Researcher at OpenAI on the mid-training team, previously working on post-training and reinforcement learning including WebGPT, ChatGPT with Browsing, and GPT-4.

Chujie Zheng is an incoming senior researcher at Alibaba Group. His academic homepage says he is finishing a Ph.D. at the University of Wisconsin-Madison and works on large language model reasoning, alignment, and reinforcement learning.

Research scientist at NVIDIA working on AI systems and large-scale machine learning, with research spanning distributed systems, deep learning, and networking.

Dibya Ghosh is a machine learning researcher at Cohere and a PhD student in computer science at UC Berkeley advised by Sergey Levine. His work spans reinforcement learning and large language models, with a focus on how foundation models can improve learning agents.

Diyi Yang is an assistant professor of computer science at Stanford University. Her research focuses on natural language processing and machine learning, especially human-centered AI, social computing, and computational social science. She earned her PhD in language technologies from Carnegie Mellon University.

Emilie Grave is a research scientist at FAIR. Her research interests include representation learning, natural language processing, and machine learning.

Postdoctoral fellow at Johns Hopkins University and incoming assistant professor at UNC Chapel Hill whose work focuses on multilingual NLP, grounded language understanding, and societal impacts of language technologies.

Han Bao is a research scientist at DeepSeek AI. His homepage says he works on machine learning theory, including out-of-distribution generalization, robust machine learning, self-supervised learning, and learning-based control.

Researcher currently at Tencent Hunyuan with public work in natural language processing, structured information extraction, and large language models.

Engineer on the Qwen team at Alibaba Cloud.

Member of Technical Staff at OpenAI and co-instructor of DeepLearning.AI's ChatGPT Prompt Engineering for Developers and Building Systems with the ChatGPT API courses; listed as a co-author of the GPT-4 Technical Report.

Iz Beltagy is an NLP researcher known for work on OLMo, Longformer, SciBERT, and other open language technologies. His public profile highlights research on open language models, scientific NLP, and long-context modeling.

Research scientist at OpenAI interested in general intelligence; previously studied computer science and cognitive science at Stanford and UC Berkeley.

PhD student at Tsinghua University researching multimodal large language models, digital avatars, and 2D/3D content generation; previously an AGI student researcher at DeepSeek AI who led DreamCraft3D and contributed to DeepSeek-VL.

PhD student at Shanghai Jiao Tong University advised by Prof. Xueqi Cheng. Her research interests include retrieval and agents, multimodal large language models, and biomedical large language models, and she is currently an intern at DeepSeek.

Research scientist at OpenAI working on core post-training and previously on pre-training, with interests in personalized and safe AI.

Lewis Tunstall is a principal scientist at Cohere Labs who works on open-source language models, evaluation, and multilingual NLP.

Researcher at DeepSeek AI and incoming Ph.D. student at the University of Hong Kong working on efficient and trustworthy LLMs, multimodal large language models, and reasoning.

Research scientist at Meta FAIR focused on multilinguality, machine translation, speech, and web-scale processing; previously a postdoctoral scholar at Stanford's Center for Research on Foundation Models.

Technical staff at OpenAI interested in the theoretical foundations and algorithms for large language models and reinforcement learning.

Mingxiao Li is a machine learning researcher focused on vision-language models, generative models, and multimodal learning. His public homepage lists a PhD at KU Leuven, and public research outputs also list him with Moonshot AI Ltd. affiliation.

Empirical AI researcher at the Allen Institute for AI whose work focuses on post-training, synthetic data, and evaluation.

Machine learning researcher and engineer; contributed to the GPT-4 Technical Report; previously an MSc by Research student at the University of Oxford Department of Computer Science.

Founding member of OpenAI and vice president of product who writes publicly about building things and machine learning.

Saurabh Pan is an AI researcher at FAIR Meta and a PhD student at Carnegie Mellon University. His work focuses on self-supervised learning, generative modeling, multimodal learning, and representation learning.

Research software engineer at Google DeepMind working on machine learning for code and formal reasoning; completed a PhD at TU Darmstadt on uncertainty quantification in deep learning.

Technical staff at OpenAI working on machine learning research, large language models, multimodal models, and robotics.

Research scientist at OpenAI working on pretraining and reasoning; previously studied computer science at Stanford University.

Member of Technical Staff at OpenAI focused on safety evaluations, economic impact evaluations, and democratic inputs to AI.

Software engineer at NVIDIA with public work spanning machine learning systems and large language models, including Nemotron-4.

Vijay Janapa Reddi is a professor of electrical engineering and computer science at Harvard University whose research spans computer architecture, systems, compilers, and machine learning.

Associate Professor in the Department of Computer Science at the University of Alabama at Birmingham whose research spans computer security, machine learning, pattern recognition, biometrics, and formal methods.

Research scientist at DeepSeek interested in post-training, tool use, and in-context learning.

Wen Ouyang is a Vice President of AI at Tencent and Director of the Visual Computing Center, where he leads the Hunyuan multimodal foundation model team. His research covers computer vision, multimodal models, and visual understanding.

Assistant Professor at the NYU Courant Institute of Mathematical Sciences. He studies formal models of intelligence, including language, learning, and efficient reasoning, and previously worked as a research scientist at Ai2.

Xiang Lisa Li is a researcher focused on controllable and steerable language models. Her public profile highlights work including Diffusion-LM, Prefix-Tuning, Contrastive Decoding, and evaluation methods such as AutoBencher.

Research scientist at DeepSeek AI focused on multimodal large language models, reinforcement learning, and efficient post-training.

Yunxing Dai is a researcher at OpenAI and a co-author of the GPT-4 Technical Report. His public homepage and Google Scholar profile provide verified research identity links.

Researcher in natural language processing and pre-trained language models, with public academic work from Tsinghua University and related NLP publications.

Research scientist at Cohere working on large language models; previously a postdoctoral researcher in machine learning at Carnegie Mellon University.

Zhiniu Wen is a research scientist at DeepSeek. His homepage says his research interests include natural language processing, machine learning, large language models, and their applications.

Adriana Hummel is a PhD student in computer science at Stanford University working on efficient and trustworthy AI systems.

Anjali Gupte is a PhD student in computer science at the University of Southern California whose research focuses on trustworthy AI, natural language processing, and information retrieval.

Public sources identify Caia Costello as a Stanford computer science MS student and quote her in 2026 as an Applied ML Researcher at Lambda; she is also a coauthor of OLMo Hybrid.

Research Scientist at Google DeepMind working on machine learning and artificial intelligence.

Zizheng Pan's homepage says he has worked on multimodal LLMs at DeepSeek since 2024. The same page says he previously completed a PhD in Computer Science at Monash University and a B.E. in Software Engineering at Harbin Institute of Technology, Weihai.

ByteDance researcher working on high-performance inference systems, AI compilers, and distributed systems; completed a PhD in computer science at Peking University in 2024.

PhD candidate at the University of Washington and research scientist at Cohere working on natural language processing and machine learning.

Ilge Akkaya is a research scientist at OpenAI working on reinforcement learning and robotics. His personal website lists a PhD in EECS from UC Berkeley and a BS in Electrical and Electronics Engineering from Bilkent University.

Noah A. Smith is a computer scientist and professor at the University of Washington, where he serves as Vice Provost for Artificial Intelligence and co-directs the OLMo open language modeling effort with Ai2. His research focuses on natural language processing, machine learning, and evaluation methodology.

Co-founder and CEO of Mistral AI and a researcher on efficient large language models and mixture-of-experts systems.

David Atkinson is a senior research scientist at Ai2 working on multimodal learning, document understanding, visual question answering, and natural language processing.

Peter Clark is Senior Director for AI at the Allen Institute for Artificial Intelligence (Ai2), where he works on natural language understanding, reasoning, and question answering.

Mistral AI's about page lists Guillaume Lample as one of the company's three founders. His OpenReview profile lists expertise in machine translation and natural language processing and a PhD in computer science at Universite Pierre et Marie Curie - Paris 6.

Li Dong is a Microsoft Research principal researcher focused on human language technologies and machine intelligence.

Yichang Zhang is a research scientist in Alibaba's Tongyi Lab and part of the Qwen team. His public profiles describe work on machine reasoning, agent systems, post-training, synthetic data, evaluation, large language models, multimodal learning, and perception.

Research scientist at DeepSeek AI working on multimodal large language models and end-to-end autonomous driving. Earned a PhD in computer science from the Chinese University of Hong Kong.

Ashish Sabharwal is publicly listed as Principal Researcher at the Allen Institute for AI. Public sources also list him as a coauthor of the OLMo 3 technical report.

Alisa Liu researches language models, including tokenization, data creation, and inference-time adaptation.

Aman Rangapur says he works on language models at Ai2 with a focus on modeling, scaling, and infrastructure, and lists prior research roles at Illinois Institute of Technology and VIT-AP.

Xin Dong's homepage says he leads a research team on LLM training at Seed at ByteDance. It also states that he earned a Harvard PhD in 2023 and previously worked at NVIDIA, Meta, and Tencent.

Yoram Bachrach is a research scientist at Meta in London focused on LLM agents and multi-agent reasoning. He previously worked at Google DeepMind and Microsoft Research in Cambridge.

Co-founder of Twenty Labs. His homepage says he previously worked as a research scientist at Google DeepMind, after earlier production machine learning work on Gmail Spam.

Suchir Balaji was a Member of Technical Staff at OpenAI (Nov 2020 to Aug 2024). His personal site states he studied Computer Science at UC Berkeley (2017 to 2021).

OpenAI staff member whose public speaker bio says she ran the Artist Access Program; earlier roles included Apple and journalism work at WIRED and USA TODAY.

Vice President of Applied Deep Learning Research at NVIDIA, leading work on conversational AI, generative AI, and accelerated deep learning software.

Researcher at Salesforce AI Research and coauthor of the xLAM-2 Technical Report.

Co-founder and CEO of Anthropic.

Researcher at Salesforce AI Research and coauthor of the xLAM: A Family of Large Action Models to Empower AI Agent Systems.

Machine learning scientist at Ai2 working on reinforcement learning, language models, and online social systems.

Researcher and engineer at Mistral AI focused on distributed machine learning and efficient large language models.

Research scientist at DeepSeek.

First-year Ph.D. student in Information Engineering at the Chinese University of Hong Kong advised by Dahua Lin and Jifeng Dai. His research interests include understanding and building intelligence in multimodal large language models.

Shaohan Huang is a senior researcher in the General Artificial Intelligence Group at Microsoft Research Asia in Beijing. OpenReview lists him as a Microsoft researcher and a former master's student at Beihang University.

Diogo Almeida is an AI researcher and a co-author of the InstructGPT paper (arXiv:2203.02155).

NVIDIA Research identifies Alexander Keller as a senior director of research, formerly chief scientist at mental images and previously a professor at Ulm University. His research interests are at the intersection of graphics, communications, and machine learning.

Mary Phuong's 2026 MATS mentor profile describes her as a research scientist at Google DeepMind working on frontier safety loss-of-control problems, including AGI control, security, and monitoring.

Yanhong Li is a pre-doctoral researcher at the Allen Institute for AI working on data-efficient pretraining, language model efficiency, and hybrid model theory.

Publicly listed as a researcher at the Allen Institute for Artificial Intelligence and named on the OLMo 3 author list.

Pavlo Molchanov leads deep learning efficiency work at NVIDIA Research, with public profiles covering LLM and VLM efficiency, model compression, adaptive inference, and earlier computer vision research.

Scott Geng's homepage identifies him as a University of Washington PhD student and visiting researcher at FAIR; the OLMo 3 technical report lists him as a coauthor.

Teng Xiao is a Young Investigator at the Allen Institute for AI and the University of Washington. His homepage says his research interests are in machine learning, natural language processing, and reinforcement learning.

Myle Ott is a research scientist at Meta working on the Llama models. His interests include scalable optimization, distributed systems, and language model pretraining.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Software engineer at OpenAI focused on inference. Previously studied computer science at Princeton University.

Machine learning researcher and PhD student at the University of Cambridge focused on multilingual and equitable NLP, especially for low-resource languages such as Filipino. He previously worked on open language model efforts at Ai2 including Tulu 3 and OLMo 2.

Researcher at OpenAI who led InstructGPT and GPT-4 post-training. He previously co-founded Merlyn Mind and was an engineering director at Quora.

Lucas Beyer is an ML researcher at Google DeepMind in Zurich. His public homepage highlights prior work at Google Brain and a PhD at ETH Zurich.

Maarten Sap is an assistant professor at the University of Washington and a senior research scientist at the Allen Institute for AI. His work focuses on human-centered language technologies and social NLP.

Nick Ryder is VP of Research, Foundations at OpenAI and a contributor to GPT-4. He previously studied mathematics at UC Berkeley and Rice University.

Research scientist at Google DeepMind on the Gemini team, working on multimodal AI.

Engineer and founder who previously worked at OpenAI, Palantir, and Lyft and now builds the AI search startup Basalt. He publishes public writing on AI products and software on his personal site.

Research scientist at DeepSeek working on post-training and reinforcement learning, with interests in systems and AI for science.

Algorithm expert at Alibaba Group working on computer vision, multimodal learning, and large language models.

DeepSeek report author whose DBLP record includes DeepSeek LLM, DeepSeekMath, DeepSeek-Coder-V2, DeepSeek-V3, DeepSeek-R1, Janus, and JanusFlow work.

DeepSeek report author whose DBLP-linked publication record includes DeepSeek LLM, DeepSeek-Coder-V2, Janus, DeepSeek-V3, and DeepSeek-R1 work.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

DeepSeek report author whose DBLP record includes DeepSeek LLM, DeepSeekMath, DeepSeek-Coder-V2, DeepSeek-V2, DeepSeek-V3, and DeepSeek-R1 work.

Alibaba Qwen report author whose DBLP profile identifies an Alibaba Group DAMO Academy affiliation and Qwen technical report authorship.

Alibaba Qwen report author whose DBLP profile identifies an Alibaba Group affiliation and Qwen technical report authorship.

Alibaba Qwen report author whose DBLP record includes Qwen2.5-VL and Qwen technical report work on multimodal and large language models.

Google researcher whose official profile says he joined Google in September 2008 and has been with Google Brain since January 2015, with research interests spanning information retrieval, machine learning, machine translation, and natural language processing.

Research engineer at DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

DeepSeek report author whose DBLP publication record includes DeepSeek LLM, DeepSeekMoE, DeepSeek-V2, DeepSeek-V3, and DeepSeek-R1 work.

DeepSeek report author whose DBLP record includes DeepSeek LLM, DeepSeekMoE, DeepSeek-Coder-V2, DeepSeek-V3, and DeepSeek-R1 work.

DeepSeek-AI researcher whose DBLP profile lists a DeepSeek-AI affiliation and DeepSeek-Coder, DeepSeek-V2, and DeepSeek-V3 authorship.

Researcher on Alibaba's Qwen team focused on pre-training and post-training for multimodal large language models and reasoning.

Alibaba Qwen report author whose DBLP profile identifies an Alibaba Group affiliation and Qwen technical report authorship.

DeepSeek report author whose DBLP record includes DeepSeek LLM, DeepSeek-Coder, DeepSeek-Coder-V2, DeepSeek-V2, DeepSeek-V3, and DeepSeek-R1 work.

DeepSeek-AI researcher whose DBLP profile lists a DeepSeek-AI affiliation and DeepSeek LLM, DeepSeek-V2, and DeepSeek-V3 authorship.

Co-author of the BitNet b1.58 2B4T Technical Report; the paper's author note states that S. Ma is with Microsoft Research.

Andrea Vallone is publicly credited on OpenAI's GPT-4 safety and policy evaluations, and late-2025 to early-2026 reporting said she left OpenAI for Anthropic's alignment team.

David Heineman works on the OLMo project at Ai2 and says he previously completed his undergraduate studies at Georgia Tech.

Weijia Shi is a Ph.D. candidate at the University of Washington. Her research focuses on building augmented and modular architectures to improve the quality, efficiency, and capabilities of language models.

Dieter Schwarz Foundation Professor and Senior Fellow in Stanford Computer Science and HAI. Her public homepage notes previous roles as professor at the University of Washington and senior director at Ai2.

Public conference bios describe Benjamin Mann as a co-founder and member of the technical staff at Anthropic. They also describe earlier OpenAI work on infrastructure, efficiency, and safety for GPT-3.

Research scientist at DeepSeek with public GitHub projects on large language models and AI systems.

Hamish Ivison's homepage says he is a PhD student in Computer Science and Engineering at the University of Washington working on natural language processing and post-training for language models. Public sources also list him as a coauthor of OLMo 3.

Ian Magnusson's public site says he does AI research at the University of Washington and the Allen Institute for AI, focused on language-model science and evaluation.

Niklas Muennighoff researches language models and evaluation at Stanford and has publicly led open-model work including OLMoE.

Akhil Mathur is a postdoctoral research scientist at Meta FAIR whose public homepage highlights work in natural language processing and machine learning.

Research scientist at Ai2 working on language models and open research infrastructure. His interests include natural language processing, machine learning, and building reliable open-source systems.

Engineer at OpenAI. Formerly worked on generative AI at Disney and on data science projects with organizations including MIT and Tufts, and studied at MIT.

Research scientist at Thinking Machines Lab with prior language-model work at OpenAI and earlier quantitative research at Bridgewater. Her public profile highlights interests in scaling language models, new architectures, and adaptive inference.

Research scientist at Meta AI working on applied mathematics, machine learning, and artificial intelligence.

Research scientist at FAIR Meta and teacher affiliated with ENS, INRIA, and PSL.

Braden Hancock is a researcher at Google DeepMind whose public homepage highlights work on large language models, weak supervision, and knowledge representation.

Cameron Raymond is a software engineer at OpenAI. His personal site says he previously worked at Asana, led developer experience at Stripe, and is an author of Staff Engineer.

Research scientist at Ai2 focused on natural language processing, commonsense reasoning, long-form generation, narrative intelligence, and text-based games.

Research manager at OpenAI with a public site covering publications and projects.

Audio research leader at OpenAI. She previously worked on MuseNet and Jukebox, and earlier studied physics at Princeton and neuroscience at Stanford before a professional career as a classical pianist.

Research Scientist at OpenAI working on deep learning theory, AI alignment, and large language models; he previously completed a PhD at Stanford advised by Percy Liang.

Principal research scientist at NVIDIA working on recursive intelligence, test-time reasoning, AI for biology, multimodal generation, and code generation.

David Karamcheti is a research scientist at Google DeepMind whose public homepage highlights work on multimodal foundation models and embodied intelligence.

Researcher at OpenAI working on multimodal and agentic systems. He previously worked on machine learning systems and video understanding, and is completing a PhD at Columbia University.

David Wadden is an assistant professor at the University of Washington working on natural language processing and AI systems for science and high-stakes domains. His public profile highlights information extraction, scientific NLP, and trustworthy language model applications.

Research scientist at OpenAI focused on multimodal reinforcement learning and natural language processing; PhD candidate at Stanford University.

Distinguished engineer on Google's Gemini LLM team working on machine learning systems, generative AI, and data center infrastructure.

Edward J. Hu is a machine learning researcher known for efficient adaptation methods for large language models, including LoRA and QLoRA. His public profile focuses on parameter-efficient fine-tuning, model editing, and practical LLM systems.

Member of Technical Staff at OpenAI working on large language models. He has also worked on software at YouTube and Google and studied computer science at Stanford University.

Research scientist at Google DeepMind working on language models, multimodal learning, evaluation, and alignment.

OpenAI team member in the San Francisco Bay Area and co-author of the GPT-4 Technical Report.

Member of Technical Staff at OpenAI. Previously at New York University, where he completed a PhD in computer science advised by Kyunghyun Cho. His interests include natural language processing, machine learning, and deep learning.

Senior Staff Software Engineer at Google working on machine intelligence, data management, and large-scale machine learning systems.

Hrant Khachatrian is a machine learning researcher and engineer at FAST and a co-founder of YerevaNN, with work spanning natural language processing, computer vision, and efficient language models.

Engineer at OpenAI credited in the GPT-4 technical report for reliability engineering. Previously worked on Google App Engine and at LinkedIn, according to his PyCon 2011 speaker profile.

Software engineer at Meta building intelligence for wearables; he previously worked on developer infrastructure for language models and assistant products, as well as on-device NLP systems.

Vice President of Learning and Perception Research at NVIDIA, leading work in computer vision, graphics, and machine learning.

Jianmo Ni is a researcher focused on information retrieval, question answering, and large language model systems. His public profile highlights retrieval-augmented generation, ranking, and efficient NLP methods.

PhD student in Computer Science at Stanford University and affiliated with OpenAI. Her research focuses on natural language processing and machine learning, and she is a co-author of the GPT-4 Technical Report.

Karthik Pattabiraman is a professor of computer science at the University of British Columbia whose research spans software engineering, dependable distributed systems, systems performance, and software security.

Researcher focused on world models, 3D generation, and neural rendering. He is a founding member of World Labs, previously worked at Google on 3D asset generation, and received a PhD from the University of Washington in 2021.

Liam Fedus is a research scientist at OpenAI. OpenAI's staff page says his research interests include reinforcement learning and language models, with a focus on improving capabilities, safety, and robustness.

Lilian Weng is vice president of research at OpenAI. OpenAI's staff page says she works on AI systems that can mimic and reason about our world to improve intelligence.

Member of Technical Staff at OpenAI focused on advancing the capabilities of large language models.

Research scientist at Mistral AI and PhD candidate at Mila whose interests include causal representation learning, world models, and reinforcement learning.

Engineer and product builder who has worked on ChatGPT, Codex, the OpenAI API, and developer tools. He publishes writing and code on his personal site and GitHub.

Machine learning researcher and engineer whose public work includes multimodal models, robotics, and reinforcement learning, including research at Cohere.

Peter West is a PhD candidate at the University of Washington studying aligned, grounded, and trustworthy language models. His work focuses on evaluation, human feedback, model behavior, and safer NLP systems.

Research scientist at FAIR Meta working on multimodal learning, image-text retrieval, and language technologies.

Member of technical staff at NVIDIA Research focused on language models, deep learning, and efficient training systems.

Research engineer at Alibaba Tongyi Lab focusing on pre-training, post-training, and efficient architecture for large language models.

Researcher at DeepSeek and incoming assistant professor at the University of Hong Kong specializing in language, vision, and speech.

Researcher whose public work spans information retrieval, recommendation systems, and large language models.

Researcher at OpenAI focused on large language models and embodied AI. Her public background includes AI and recommendation work at TikTok, computer vision and robotics research at Stanford, and an ML master's at Princeton.

Research scientist at the Allen Institute for AI working on large language models, multilingual NLP, machine reasoning, and model evaluation.

Research scientist at OpenAI.

Shusheng Yang is a research scientist in Tongyi Lab at Alibaba Group. His work focuses on natural language processing and machine learning, especially pre-trained language models, text generation, and efficient NLP.

Taya Hartman is a product and brand designer whose public portfolio spans digital, visual, and interactive work. Public sources tie her to Cohere as a senior designer, and she is credited as a contributor to the Command A technical report.

Thomas Degry is a design engineer at OpenAI based in San Francisco. Public profiles also describe prior work as a design engineer at Stripe and as tech lead for openai.com.

Tomi Pott is a research engineer at Meta Research whose public homepage highlights work in multi-agent reinforcement learning, deep learning, and AI systems.

Principal scientist at Cohere and adjunct professor at McGill University, with research spanning NLP, machine learning systems, speech, and biometrics.

Research scientist at OpenAI working on reinforcement learning and efficient machine learning; previously completed a PhD at UC Berkeley advised by Sergey Levine.

Researcher in multimodal large language models at the Alibaba Qwen team and student at Johns Hopkins University.

Senior member of technical staff at OpenAI focused on machine learning systems and AGI. He previously co-founded DeepGPU and publishes public writing and code on his website and GitHub.

Research scientist at OpenAI focused on applying AI to medicine and science; previously worked on AI for vision, language, healthcare, and robotics.

Research intern at DeepSeek and a Tsinghua University undergraduate focused on machine learning systems and large language model inference.

Ph.D. student in Computer Science at Zhejiang University and researcher on the Qwen series at Alibaba Group.

Kyle Lo's public homepage says he formerly served as a research scientist at the Allen Institute for AI, where he co-led OLMo. It describes current work on large-scale pretraining, data mixing, benchmark validity, and research-supporting data and software artifacts.

Yanping Huang's OpenReview profile says he has been an engineer at Google since 2015 and lists research interests in machine learning systems, machine translation, and image classification. Public report records also list him as a co-author on the DeepSeek-V3 technical report.

Jakub "Jake" Poznanski identifies himself on his personal site as a Carnegie Mellon computer science graduate and describes leading an OCR toolkit on GitHub.

Member of Technical Staff at OpenAI. His public homepage lists research and publications spanning GPT-4, differentiable physics, and scientific machine learning.

Michael Schmitz is a software engineer and manager in the Pacific Northwest. His personal site says his current position is Director of Engineering at the Allen Institute for AI.

Jared D. Kaplan is the co-founder and chief science officer of Anthropic. Public biographies also describe his earlier work on GPT-3 and Codex at OpenAI and his background in theoretical physics.

Kevin Farhat's homepage says he is a research engineer at Ai2 working on language models, distributed AI, and privacy-preserving training. Public sources also list him as a coauthor of FlexOlmo.

Works on high-performance LLM inference and AutoDeploy at NVIDIA; previously led efficient-AI work at OmniML and earned graduate degrees at MIT CSAIL.

Jacob Devlin is a research scientist at Google DeepMind whose work focuses on language models, long-context modeling, and tool use.

Public profiles list Kim Malfacini as head of product policy at OpenAI, with earlier work in public policy and trust and safety for AI systems.

Anthropic co-founder and chief architect working on large-scale model training, research productivity, and reinforcement learning infrastructure.

Partner Research Manager at Microsoft Research Cambridge, with official Microsoft pages describing work in artificial intelligence, computer vision, and human language technologies.

Jason Baldridge is a Research Scientist at Google DeepMind working on natural language understanding, multimodal learning, and evaluation.

CEO of the Allen Institute for AI and professor of computer science at the University of Washington. His work spans computer vision, multimodal learning, reasoning, and embodied AI.

Alibaba researcher working on large language models and multimodal pretraining; public research profiles connect An Yang to Qwen-related work and earlier study at Peking University.

Researcher on Alibaba's Qwen team focused on large language models and NLP, with public research profiles listing a Nankai University background.

Zhifeng Chen's public homepage describes him as a distinguished software engineer at Google Brain focused on large-scale computer systems and machine learning applications.

Timothée Lacroix is a machine learning researcher and one of the founders of Mistral AI.

Computer scientist and engineer credited on OpenAI's GPT-4 public contributions page; OpenAI's 2016 team update says he previously led Dropbox's core file sync team after earlier work in Pieter Abbeel's Berkeley robotics lab.

Chief Technology Officer at Google DeepMind, with work spanning machine learning and reinforcement learning.

Researcher at DeepSeek interested in efficient large language models and multimodal large language models.

Research scientist at DeepSeek.

Member of Technical Staff at Google DeepMind working on machine learning, natural language processing, and large language models.

ML researcher at DeepSeek.

Hongkun Yu is a research scientist at Google Research. His official Google Research profile says his work lies at the intersection of machine learning, signal processing, and sequence modeling.

Pradeep Dasigi is a research scientist on the AllenNLP team at Ai2. His homepage says he has been actively involved in OLMo and Tulu and currently focuses on post-training language models.

OpenAI co-founder and president whose public work spans the OpenAI API, Codex, Gym, OpenAI Five, and broader large-scale model systems.

VP of Research at Google DeepMind working on robotics and embodied intelligence, with expertise in machine learning, reinforcement learning, neuroscience, and computer vision.

Rui Xin's public homepage identifies him as a PhD student at the University of Washington working on reinforcement learning, privacy-preserving machine learning, and memorization.

Sam Altman is the CEO of OpenAI.

Shayne Longpre's public profiles identify him as a PhD candidate at MIT focused on data-centric AI, language models, and their societal impact.

Head of AI for Civil Society and Philanthropy at the OpenAI Foundation. An OpenAI update says she previously served as Vice President of Global Impact at OpenAI.

Former Chief Communications Officer at OpenAI. Public reporting says she joined OpenAI in 2021 after seven years at Apple and announced her departure in December 2025.

Mohammad Bavarian is a researcher at OpenAI. His personal site states that he earned a PhD from MIT in 2017 and previously worked as a researcher at Rubrik.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Saumya Malik is an incoming postdoctoral scholar at Johns Hopkins University and recently completed a PhD in the Machine Learning Department at Carnegie Mellon University. Her interests include interpretability, evaluation, reward learning, and language model agents.

DeepSeek team member and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Researcher at Qwen, Alibaba Group since 2021, with publications on large language model evaluation and pre-training data management.

Machine learning researcher whose public profile highlights work across Berkeley AI Research, RISELab, Sky Computing, and the Ray team.

Research Scientist at Ai2 focused on natural language processing, reasoning, and grounded commonsense understanding.

Sandeep Subramanian is an Assistant Professor at MBZUAI whose research focuses on grounded language generation, multimodal learning, and large language models.

Research scientist at Alibaba DAMO Academy focusing on aligning and scaling superintelligence.

Member of Technical Staff at OpenAI working on machine learning, reinforcement learning, natural language processing, and large language models.

Research scientist at OpenAI interested in AI safety, alignment, governance, and technical safety.

Computer scientist and AI researcher who co-founded OpenAI and served as its chief scientist.

Member of the Qwen Team at Alibaba Group and a Ph.D. candidate at the Institute of Automation, Chinese Academy of Sciences. His research interests include multimodal reasoning and agents.

Research scientist at DeepSeek AI interested in language models, multimodal large language models, and deep generative models.

Vice president at Google DeepMind in London working on machine learning and reinforcement learning. His public profile notes work spanning policy-gradient methods, distributed and generative models, and robotics.

Research scientist at Meta working on AI agents, language, and reinforcement learning.

Researcher at Alibaba Qwen; formerly a postdoctoral researcher at the University of Cambridge and a PhD in NLP at the University of Edinburgh.

Akari Asai's public homepage identifies her as a research scientist at OLMo at Ai2 for 2025-2026 and an incoming assistant professor at Carnegie Mellon University starting in fall 2026.

Leads OpenAI Labs, a research team prototyping new interfaces for people and AI. She studied computer science and applied math at Stanford.

Senior research scientist at AI2 on the AllenNLP team. His homepage says his work focuses on question answering, semantic parsing, and reasoning over open-domain text.

Nikolaus Binder is a senior research scientist at NVIDIA whose public research profile focuses on quasi-Monte Carlo methods, photorealistic image synthesis, ray tracing, and rendering algorithms.

Research scientist in Tongyi Lab whose official profile highlights multimodal large language models, efficient reasoning, and AI infrastructure.

Christopher Clark is a researcher working on language models, efficient inference, and trustworthy NLP systems. His public profile highlights work at the intersection of NLP, efficiency, and model evaluation.

Research director at Google working on music AI, multimodal generation, and human-AI interaction. He co-founded the Magenta project and has led widely used work on music generation with neural networks.

OpenAI researcher and software engineer known for creating Triton, an open-source GPU programming language, and co-authoring the GPT-4 Technical Report.

Research scientist focused on foundation models and multimodal large language models; his homepage notes earlier work at DeepSeek AI and current research at the University of Southern California.

Wenfeng Liang, also known as Liang Wenfeng, is linked to DeepSeek technical reports in LLMpeople and is identified in public references as the founder and CEO of DeepSeek.

Alibaba Qwen report author listed on Qwen, Qwen2.5, Qwen2.5-1M, Qwen3, Qwen3 Embedding, QwQ-32B, and Qwen-VL reports, with report-backed work on large language models, embeddings, reranking, and multimodal models.

Researcher at DeepSeek and former master's student in EECS at Peking University. Public profiles list work on LLMs, multimodal systems, transformers, BERT, and machine translation.

Zeyu Cui is listed as an author of the Qwen technical report Qwen3 Technical Report.

Public report authorship links Jie Zhou to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Alibaba Qwen report author listed on Qwen, Qwen2.5, Qwen2.5-1M, Qwen3, and Qwen-Image reports, with report-backed work on large language models, long-context models, and image generation.

Alibaba Qwen report author listed on Qwen, Qwen2.5, Qwen3, Qwen-VL, and Qwen-Image technical reports, with report-backed work on large language models, vision-language models, and image generation.

DeepSeek report author listed on DeepSeek LLM, DeepSeekMoE, DeepSeek-Coder, DeepSeek-V2, and DeepSeek-V3 reports, with report-backed work on large language models, mixture-of-experts systems, and code models.

Alexandre Sablayrolles is listed as an author of the Google technical report PaLM 2 Technical Report.

Senior research scientist at NVIDIA focused on large language models, reinforcement learning, and inference-time scaling for AI agents. His public NVIDIA author page also notes prior work on robotic grasping, pose estimation, and language understanding.

Armand Joulin is listed as an author of the Meta AI technical report Llama 2: Open Foundation and Fine-Tuned Chat Models.

Public report authorship links Brennan Saeta to the Gemma 2: Improving Open Language Models at a Practical Size at Google.

Public report authorship links Jason Wei to the Gemma 3n Technical Report at Google.

Qinyu Chen is listed as an author of the DeepSeek technical report DeepSeek-V3 Technical Report.

Xingkai Yu is a report-backed author in the LLMpeople atlas, connected through DeepSeek technical reports including DeepSeek-V3, DeepSeek-V2, DeepSeek LLM, and DeepSeekMoE; his public GitHub profile lists DeepSeek affiliation.

Researcher at Alibaba working on foundation models and agents for enterprise applications.

Google Gemini report author listed on Gemini, Gemini 1.5, RecurrentGemma, and CodeGemma technical reports, with report-backed work on multimodal models, long-context models, efficient architectures, and code models.

Alibaba Qwen report author listed on Qwen, Qwen2.5, Qwen2.5-1M, and Qwen3 technical reports, with report-backed work on large language models, long-context modeling, and reasoning.

DeepSeek report author listed on DeepSeek LLM, DeepSeek-Coder, DeepSeek-V2, and DeepSeek-V3 technical reports, with report-backed work on code models and large language models.

Z.ai report author listed on GLM-Z1, GLM-4.5, GLM-4.1V/4.5V, and GLM-5 materials, with report-backed work on reasoning, coding, agentic, and multimodal models.

Z.ai report author listed on GLM-Z1, GLM-4.5, GLM-4.1V/4.5V, and GLM-5 materials, with report-backed work on reasoning, agentic, and multimodal models.

Clemens Winter writes publicly about reinforcement learning and machine learning systems, and official OpenAI materials credit him on GPT-4 and GPT-4.5 work. Accessible public sources do not clearly establish a current employer.

Research scientist in Tongyi Lab whose official profile highlights post-training and multimodal large language models.

Researcher at Moonshot AI and co-author of the Kimi K2.5 report on visual agentic intelligence.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Researcher at Meta whose public OpenReview profile lists previous research roles at Google and Baidu.

Groundlight AI lists Tyler Romero as Lead ML Engineer. Public sources also list him as a coauthor of OLMo 3.

Co-founder and CEO of Cohere; previously a doctoral student at Oxford and a student researcher and intern at Google Brain.

Researcher at Cohere working on machine learning, natural language processing, and computer vision.

Devendra Singh Chaplot is a research scientist at Mistral AI working on language models and multimodal AI.

Research scientist at OpenAI with a background in theoretical physics, computational neuroscience, and theoretical AI.

Mikhail Pavlov is publicly credited on OpenAI's GPT-4 contributions page as software correctness lead and on GPT-4V technical work as a scaling engineering lead.

Xuezhi Wang is a Research Scientist at Google DeepMind whose public work focuses on reasoning and systematic generalization in language models, along with robustness and fairness in natural language processing. She received her PhD from Carnegie Mellon University in 2016.

Professor at Stanford University and senior director at the Allen Institute for AI. Her research spans natural language processing, commonsense reasoning, and multimodal AI.

Research scientist at Alibaba Qwen working on LLM post-training, RLHF, reasoning, and evaluation; incoming assistant professor at Renmin University of China.

Member of Technical Staff at DeepSeek focusing on large language models and reinforcement learning.

Research scientist at Meta working on post-training and model personalization. He previously worked on retrieval systems, recommendations, and ranking, and earned his Ph.D. from Stanford University.

Staff research scientist at Meta whose work focuses on democratizing natural language processing tools, especially for low-resource languages.

Member of the Cybersecurity Policy and Insights team at OpenAI covering the intersection of technology, international security, and geopolitical competition.

Alexander Wettig is a Princeton computer science PhD student advised by Danqi Chen. His homepage says he studies language models and their training data, previously interned at Ai2, and is currently working on training coding agents at Cursor.

Amanda Bertsch is a Ph.D. student in the Language Technologies Institute at Carnegie Mellon University. Her research focuses on making language models faster and more memory efficient at test time and improving performance on very long contexts.

Benjamin Minixhofer is a third-year PhD student at the University of Cambridge's Language Technology Lab. His homepage focuses on resource-efficient language models, modularity, and adaptive tokenization, and notes prior research experience at Ai2.

AI researcher at OpenAI working on reinforcement learning and reasoning.

Researcher at Moonshot AI focused on reinforcement learning and robotics. He earned a Ph.D. in robotics and machine learning from Carnegie Mellon University.

OpenAI contributor with a personal homepage and GitHub profile covering NLP and language model research.

Researcher at Alibaba DAMO Academy with a background in natural language processing, speech, and recommender systems.

Member of technical staff at OpenAI whose public profile notes a PhD in computational neuroscience from Princeton University.

Researcher at OpenAI focused on improving the efficiency and reliability of AI systems.

Researcher whose public profiles include Amazon Science and USC ISI; his work spans dialogue systems, temporal reasoning, and document retrieval.

OpenAI contributor with a personal homepage and GitHub profile covering software and AI engineering projects.

Researcher and writer focused on safe and beneficial AI; listed as a contributor to GPT-4 by OpenAI.

Research scientist at Google working on multilingual generation, machine translation, and large language model systems. His public work spans translation quality, evaluation, and scalable language technology.

Applied scientist at Cohere focused on natural language processing and machine learning.

Researcher with public work on large language models. Official Qwen materials credit her on Qwen releases, and public profiles include DBLP and OpenReview.

Member of technical staff at OpenAI. Previously pursued a PhD at Stanford University, focusing on practical reinforcement learning and bandits.

Engineer at OpenAI working on the API; previously built products and customer experience systems at Stripe and Instacart.

Vishal Kuo is a member of technical staff at OpenAI.

Member of technical staff at xAI; previously a research scientist at DeepSeek AI and a PhD student in Computer Science and Engineering at the University of Michigan.

Ph.D. candidate in computer science at Princeton University working on LLM agents and machine learning. He is a coauthor of Moonshot AI's Kimi k1.5 report.

Researcher with public work on large language models. Official Qwen materials credit him on Qwen releases, and public profiles include DBLP and OpenReview.

Tsinghua University PhD student whose public OpenReview profile lists a 2024 DeepSeek-AI research internship and interests in scalable foundation models, multi-agent systems, and controllable AIGC.

Daniel Mossing is a research scientist at OpenAI. His OpenReview profile also lists past affiliations with UC Berkeley and New York University.

Member of technical staff at OpenAI interested in empirical machine learning and exploration in reinforcement learning; previously a PhD candidate at MIT.

Staff research scientist at Google DeepMind interested in deep learning theory and applications, with a focus on scaling and reinforcement learning.

OpenAI team member and co-author of the GPT-4 Technical Report.

Senior applied research scientist at NVIDIA focused on pretraining and post-training methods for large language models, multimodal learning, and synthetic data generation.

Carolyn Zhang is a researcher focused on large language models, natural language processing, and machine learning.

Research scientist at Google DeepMind.

DeepSeek team member and co-author of the DeepSeek-V3 Technical Report.

Research scientist and engineer working on large-scale machine learning. His personal site highlights contributions to GPT-3, GitHub Copilot, and Stable Diffusion.

Clément Gehring is a research scientist at Mistral AI working on efficient, multilingual, and general-purpose language models. He is also known for influential early work on neural machine translation, including convolutional sequence-to-sequence models.

Member of technical staff at Cohere Labs, where he works on models for code, reasoning, and agents and contributes to post-training.

Dragomir Radev is an Eminent Professor of natural language processing at MBZUAI. His research spans NLP, information retrieval, question answering, and summarization, and he is also a coauthor of the Nemotron-4 15B technical report.

Research engineer at OpenAI.

OpenAI team member and co-author of the GPT-4 Technical Report.

Senior research scientist at NVIDIA focused on large language models and reasoning systems. His public NVIDIA author page notes more than eight years of machine learning work spanning NLP, forecasting, recommender systems, and computer vision.

Senior research scientist at NVIDIA working on multimodal and embodied AI, including multilingual multimodal large language models and human-centered robot learning.

Laura Buesing is a research scientist at Google DeepMind working on machine learning and computational neuroscience, with a focus on agents that remember, reason, and plan.

Manaal Faruqui is an NLP and large language model researcher whose public profile covers factuality, instruction following, conversational systems, and language understanding. His work spans large language model post-training as well as earlier research on word representations, question quality, and dialogue systems.

Researcher at OpenAI and a co-author of the GPT-4 Technical Report.

Moein Khazraee is a postdoctoral researcher at LMU Munich and a visitor at Google DeepMind. His research focuses on reliable and trustworthy machine learning for language, knowledge, and reasoning.

Senior research scientist at NVIDIA focused on embodied agent AI, simulation and rendering, computer vision, robot learning, and AI in science.

Nima Rajani is a research scientist at Ai2 whose work focuses on trustworthy, interpretable, and verifiable AI systems.

Research scientist at OpenAI focused on generative models and unsupervised learning. He studied computers, mathematics, and physics at MIT and has contributed to models including GPT-3, Jukebox, and DALL·E.

Researcher and engineer whose public homepage lists work on multimodal reasoning, robustness, and mechanistic interpretability; he was an OpenAI Resident and is credited on the GPT-4 technical report.

Inventor, author, and futurist serving as Principal Researcher and AI Visionary at Google, known for long-running work on AI, language technology, and human-computer systems.

OpenAI team member and co-author of the GPT-4 Technical Report.

Siddharth Narayan is a researcher focused on natural language processing and AI, with applications that include healthcare.

Applied research scientist at NVIDIA working on reinforcement learning for large language models, post-training, and data curation.

OpenAI team member and co-author of the GPT-4 Technical Report.

Research scientist at Amazon AGI and assistant professor at Yale School of Medicine whose work focuses on diffusion models, equivariant deep learning, and generative models for molecules and proteins.

DeepSeek team member and co-author of the DeepSeek-V3 Technical Report.

OpenReview lists Evan Pete Walsh as a researcher at the Allen Institute for Artificial Intelligence, and recent public reports credit Pete Walsh on OLMo Hybrid and related open-model work.

Yu Wan is publicly listed as an author on the Qwen2.5 and Qwen3 technical reports.

Staff scientist at Tongyi Lab, Alibaba Group, and Qwen team member working on multimodal language models, AI agents, evaluation, reasoning, and information extraction.

Chloe Anastasiades is a software engineer at the Allen Institute for Artificial Intelligence and a co-author on Ai2 papers including OLMo 3 and Ai2 Scholar QA.

Public Peking University faculty pages list Zhifang Sui as a professor in the Institute of Computational Linguistics with research interests in natural language processing and computational linguistics.

Research engineer at Meta with a verified OpenReview profile listing current affiliation at Facebook/Meta.

Ivo Danihelka is a research scientist at Google DeepMind whose public profile highlights deep learning research and machine learning publications.

Tara N. Sainath is a distinguished research scientist and director at Google DeepMind whose work focuses on speech recognition, spoken language understanding, and multimodal large language models.

Research scientist at Mistral AI working on machine reasoning and probabilistic deep learning.

Edouard Grave is a machine learning researcher whose public work spans representation learning, natural language processing, and large language models.

Research scientist at the Allen Institute for AI (Ai2) whose work focuses on natural language understanding and commonsense reasoning.

DeepSeek team member focused on pretraining, post-training, and efficient scaling for large language models.

Research scientist at DeepSeek AI. His homepage also describes him as a PhD candidate in computer sciences at the University of Wisconsin-Madison.

Engineer at OpenAI working on inference infrastructure, product engineering, and prototyping for systems including GPT-4 and DALL-E 2.

A 2024 dotAI speaker bio describes Armand Joulin as a Research Director at Google DeepMind working on Gemma, after leading FAIR EMEA at Meta.

The University of Lethbridge Experts Database lists Nawshad Farruque in Maths and Computer Science, with research expertise in large-scale GIS database management, distributed spatial query processing and optimization, software engineering, and artificial intelligence.

Official Georgia Tech and NVIDIA DLER pages list Yingyan Celine Lin as a Georgia Tech associate professor and a visiting professor collaborating with NVIDIA's deep learning research group.

Keming Lu is a research scientist at Tongyi Lab, Alibaba Group in Beijing and a co-author of the Qwen and Qwen2.5 technical reports.

AI Scientist & Observability Lead at Mistral AI.

Research scientist on the AllenNLP team at the Allen Institute for AI, focused on post-training language models.

Aäron van den Oord is a Google DeepMind researcher known for generative and sequence-model research.

Researcher at OpenAI and co-creator of DALL-E who works on multimodal generative models and image generation.

Research scientist at Google DeepMind working on multimodal and generative AI for healthcare.

Chris Bamford is a researcher at Mistral AI working on foundation models and multimodal systems.

Eric Hambro is a machine learning researcher and entrepreneur whose prior work includes contributions at Meta AI and the LLaMA project.

Member of technical staff at OpenAI whose public profile notes leadership of the MT+MX team from 2020 to 2025 after earlier engineering work at Google.

Research scientist at OpenAI working on reinforcement learning and robotics, with a PhD from UC Berkeley.

Senior research scientist at NVIDIA focused on language and vision models and applied multimodal AI.

Julian Schrittwieser is a Google DeepMind researcher known for reinforcement learning and game-playing systems.

Z.ai researcher focused on multimodal large language models and computer vision, with interests in large-model training and post-training.

Research scientist at Google DeepMind based in Paris, focused on deep learning and computer vision.

DeepSeek team member focused on scaling large language models, multimodal models, and large-scale reinforcement learning.

Mohammad Ghassemi is a distinguished researcher at TII, AI71, and MBZUAI in Abu Dhabi. His work spans machine learning, digital health, and trustworthy AI, and he previously held faculty roles at MIT and the University of Toronto.

Senior AI scientist at the Technology Innovation Institute and machine learning researcher at MBZUAI.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including DeepSeek-VL2, plus coauthor credit on the DeepSeek-V2 and DeepSeek-V3 technical reports.

Assistant Professor at the University of Washington whose research focuses on machine learning, AI safety, and evaluation; he is a co-lead of the OLMo language model project.

Researcher and engineer working on language models and reinforcement learning, with public work spanning Alpaca, emerging agents, and large-model evaluation.

Research scientist at Ai2 specializing in open language models, reasoning, and multi-agent systems.

DeepSeek researcher. Public OpenReview and Hugging Face profiles identify Z.Z. Ren with DeepSeek and list work on theorem proving and synthetic training data for reasoning models.

Igor Babuschkin's homepage describes him as an AI researcher, builder, and investor, and highlights Babuschkin Ventures. Public reporting also describes him as a former DeepMind researcher and former OpenAI technical staff member.

NVIDIA's public author page identifies Maksim Khadkevich as a Senior Software Engineering Manager specializing in distributed inference systems and large language models. arXiv public sources also list him as a coauthor of Nemotron-Flash.

Ai2's team directory lists Ronan Le Bras, and public report sources credit him as an author on open-language-model work.

Co-author of the OpenELM paper with author affiliation shown as Apple on the arXiv HTML version.

Member of technical staff at OpenAI working on post-training. Previously worked on climate and sustainability software and on policy and product efforts related to the electric transition.

Assistant professor at the University of California, Berkeley and research scientist at the Allen Institute for AI. Her public homepage highlights work on language models, natural language processing, pretraining, post-training, and test-time computation.

Senior research scientist at Alibaba focused on large language models and agent learning.

Assistant professor at Carnegie Mellon University and scientist at Ai2, working on natural language processing and machine learning with a focus on grounding, multilinguality, and robustness.

Machine learning engineer at FAIR at Meta AI and incoming PhD student at Carnegie Mellon University.

Abhishek Rao is a Research Scientist at Google DeepMind working on machine learning and natural language processing, with interests including structured prediction, reasoning, compositionality, and controllable generation. He has contributed to large language model research including PaLM.

Senior research director at Salesforce AI Research and associate adjunct professor at UC Berkeley.

Andras Sarkozy is a senior staff research scientist at Google DeepMind in London. His public profiles describe work on machine learning and natural language processing, with interests in code generation and reasoning in language models.

Research scientist at NVIDIA working on large language model post-training and inference.

OpenAI contributor with a personal website covering research and writing.

Ariel Herbert-Voss is a computer scientist whose public homepage notes previous work on AI safety and special projects at OpenAI, along with later work on digital humans and universal basic income initiatives.

Research engineer at OpenAI focused on reinforcement learning and human-computer interaction; previously co-founded the local-first AI startup Ted AI.

Program manager at OpenAI working across finance, legal, operations, and communications, after earlier work in philanthropy, marketing, and project management.

Public profiles list Bianca Martin as chief of staff at OpenAI, with an Oxford background in philosophy, politics, and economics.

Research scientist at NVIDIA with publications in machine learning and embodied AI.

Researcher with public work on large language models. Official Qwen materials credit him on Qwen releases, and public profiles include DBLP and OpenReview.

Researcher and engineer with public work on similarity search and large model systems. Public profiles list Zhejiang University, and DeepSeek open-source releases credit him on projects including DeepSeek-VL and DualPipe.

Research Scientist at OpenAI with public work in machine learning and generative models.

Research scientist at Google DeepMind whose work focuses on machine learning, speech, and large language models.

AI law and policy researcher and Director of Research at the Institute for Law & AI; previously held policy and legal roles at OpenAI.

Google researcher working on machine learning, computer vision, and natural language, and a co-author of the PaLM 2 technical report.

AI2 researcher working on multimodal language models, evaluations, instruction tuning, and preference alignment, and a co-author of Open Instruct.

AI researcher focused on epistemic safety for advanced AI systems, including uncertainty and out-of-distribution detection.

Researcher at Cohere working on large language models. Her public homepage highlights interests in privacy-preserving machine learning, robust machine learning, natural language processing, and reinforcement learning.

Engineer at OpenAI who spoke publicly about fine-tuning GPT-4 at DevDay.

Research scientist at Google working on machine learning and language models. His public work includes efficient model architectures, language understanding, and large-scale training.

Dhruti Sreedhar is a research scientist at Databricks whose interests include generative models, post-training, and long-context language models. Previously, she studied at MIT and IIT Madras.

Di He is a machine learning researcher whose public homepage and Google Scholar profile highlight work on large language models, efficient training, and foundation models.

Research scientist and engineer working on machine learning and distributed systems, with large-scale language model contributions including PaLM 2.

Vice President of Research at Google DeepMind. His work spans search, recommendation systems, human-computer interaction, and practical applications of large language models.

Lead researcher at OpenAI whose official profile focuses on speech and audio.

Eric Hu is a designer and creative director whose public portfolio spans technology, fashion, music, and architecture. At Cohere he served as VP of Design and is credited as a contributor to the Command A technical report; his public work also includes earlier design leadership roles at Nike and SSENSE.

Research scientist at Google DeepMind working on language models and efficient sampling and serving.

Research scientist at Meta working on large language models, large-scale reinforcement learning from human feedback, retrieval, recommendation systems, and machine learning systems.

AI researcher at Meta with public work on foundation models, optimization, and machine learning evaluation.

Research scientist at NVIDIA working on language and vision models.

Allen Institute for AI researcher working on NLP, machine learning, and AI, and a co-author of Open Instruct.

PhD student at KAUST and predoctoral researcher at DeepSeek focused on reasoning, alignment, post-training, and multimodal large language models.

Research scientist at OpenAI working on multimodal understanding, reasoning, and agents; formerly a Ph.D. student at Seoul National University.

Research engineer at OpenAI and contributor to GPT-4.

Ilia Kava is a member of technical staff at Databricks who works on language models and machine learning systems. He contributed to Databricks' DBRX open large language model research.

Research scientist at OpenAI working on reinforcement learning and AI alignment. Previously a PhD student in computer science at Harvard University.

OpenAI contributor with a public GitHub profile covering engineering projects.

Professor emeritus of computer science at Jean Monnet University whose work includes natural language processing and large language model adaptation and evaluation.

Researcher in natural language processing, low-resource languages, machine translation, and responsible AI; publicly listed as a PhD candidate at UC Santa Barbara and a co-author of Tulu 2.

Works at OpenAI on reasoning and general intelligence, and co-authored the GPT-4 Technical Report.

Member of technical staff at OpenAI whose official profile highlights multimodal models and intelligence.

Julian Martin Eisenschlos is a Research Scientist at Ai2. His work focuses on natural language processing, language models, and instruction tuning, including contributions to the Tulu 2 project.

Research scientist at Google DeepMind working on data compression, efficient language models, and multilingual modeling.

Research scientist at Amazon AGI and former Stanford University PhD student.

Staff research scientist at Meta whose work focuses on multilingual and multimodal AI, reasoning, and safety.

Research scientist at Google DeepMind working on natural language understanding and machine learning.

Research scientist at Google DeepMind working on machine learning and natural language processing.

Associate professor at ShanghaiTech University working on natural language processing and machine learning.

Professor of Electrical and Computer Engineering at KAUST whose research focuses on machine learning and AI, including edge intelligence, tinyML, efficient AI, and uncertainty-aware learning.

Program manager at OpenAI leading contracting, revenue, pricing, and finance operations, after earlier operations and finance roles at Tesla and Capchase.

OpenAI contributor with a personal website and public engineering projects.

Research scientist at Google DeepMind whose work focuses on pre-training, post-training, and reasoning for large language models.

Research scientist at NVIDIA Research working on computer vision, machine learning, and deep learning, and a co-author of the Nemotron-4 340B technical report.

Co-founder of DeepSeek who leads pre-training and post-training research, with a focus on language models, reasoning models, and reinforcement learning.

Research scientist at Mistral AI with a public publication record on Google Scholar and DBLP.

Research scientist at Google DeepMind focused on multimodal and embodied AI. His work covers computer vision, video understanding, and machine learning for interactive systems.

OpenAI contributor to GPT-4 evaluation and analysis, including Evals open-sourcing, instruction-following evaluation, and API model evaluations.

Senior staff research scientist at Google DeepMind and assistant professor at the Czech Technical University in Prague.

Senior applied scientist at NVIDIA focusing on generative and agentic AI, language models, information extraction, multimodality, and reasoning.

Merry Mou is a researcher at Ai2 whose public homepage and Google Scholar profile highlight work on language model post-training, evaluation, and open-source foundation models.

Harvard computer scientist and professor whose research spans algorithms, probability, information theory, and data streams.

Senior research fellow at the Institute for AI Policy and Strategy and former OpenAI research scientist focused on AI governance and policy.

Founder and CEO of Thinking Machines Lab and former CTO of OpenAI.

Research scientist at Google DeepMind working on natural language processing, speech, and multimodal machine learning.

Researcher at OpenAI working across multimodal systems, reasoning, and new product experiences, with earlier roles at Google and YouTube.

Head of product for ChatGPT at OpenAI. He works on ChatGPT and related product experiences, including agent-style workflows and consumer AI tools.

Research scientist at OpenAI.

Machine learning researcher at Cohere whose work focuses on large language models and post-training.

Research scientist at Cohere whose work focuses on deep learning and large language models.

Research scientist at Google DeepMind focused on learning with reward feedback and reasoning in large language models.

Research scientist working on large language models, scaling, alignment, and language; public work includes machine translation robustness, data selection, CodeGemma, and reward overoptimization in LLMs.

Pavan Balaji is a computer scientist and research leader in high-performance computing. His public profiles include work at NVIDIA and leadership of the Argonne Leadership Computing Facility, with research spanning parallel programming models, communication libraries, and runtime systems.

Prasad Sattigeri is a machine learning engineer at Snowflake working on agentic AI systems and machine learning.

Pratyusha Kamesetty is a deep learning research scientist at NVIDIA and a PhD candidate in computer science at Stanford University. Her research focuses on language models, recommendation systems, and generative AI for music and video.

Preston Tuggle is a distributed systems engineer at OpenAI.

Research scientist at NVIDIA.

Technical staff member at OpenAI. Previously completed a PhD at Stanford University and was a research fellow at the Simons Institute for the Theory of Computing.

Rishiraj Adhikary is a senior applied research scientist at NVIDIA working on AI systems and generative AI.

Research scientist at NVIDIA.

DPhil candidate in Engineering Science at the University of Oxford whose work spans cybersecurity, machine learning, and natural language semantics.

Research scientist at Meta working on language models and machine translation.

Researcher at DeepSeek focused on multimodal models, AI agents, and efficient large language models; previously worked on large-scale recommender systems at Tencent and Kuaishou.

Research scientist at Cohere working on multimodal and embodied AI, robotics, and machine learning systems.

Associate professor at UC Irvine and research director at Snowflake AI Research.

Research scientist at Cohere whose homepage highlights work on efficient and reliable natural language processing, following earlier research engineering work at Google.

Principal applied scientist at NVIDIA whose public work focuses on applied machine learning and large language models.

Machine learning researcher focused on reliable ML systems. She was a postdoc in Computer Science at Stanford and earned her PhD from MIT.

OpenAI contributor with an official OpenAI profile page; public contribution pages list work on GPT-4, GPT-4o, and DALL-E 2.

Research scientist at Cohere whose work focuses on natural language processing and language models.

Research engineer at Meta working on Llama models and generative AI. She previously completed an MS in computer science at New York University.

Research scientist at the Allen Institute for AI focused on training, evaluating, and interpreting language models, with work spanning NLP and computational social science.

OpenAI member building agentic products; previously founded the AI note-taking app Circleback and writes about AI, product, and startups.

Sina Samangooei is a machine learning researcher whose public work includes multimodal learning and open language models.

Machine learning researcher at NVIDIA focused on large language models and reinforcement learning.

Engineer and builder who co-founded comma.ai and previously led self-driving at OpenAI, with public work spanning autonomous driving, AGI, and music.

Assistant professor at Cornell Tech whose research focuses on human-AI interaction, AI copilots, and tools that help people learn, create, and make decisions with AI.

Mathematician and machine learning researcher whose NYU profile describes him as a PhD student in mathematics, advising at NYU Shanghai and a research intern at Google DeepMind; he also co-authored AlphaGeometry and the Gemma report.

Research scientist at Ai2 working on personalized language models, instruction tuning, and reinforcement learning from human feedback.

Researcher at Cohere.

Venkatesh Akella is a professor of electrical and computer engineering at the University of California, Davis and director of the Center for AI and Experimental Futures. His research includes machine learning, trustworthy AI, causal AI, computer vision, robotics, and intelligent systems.

Research scientist at Ai2 and PhD student at UC Berkeley working on language models, multilingual NLP, and evaluation.

Research scientist at Google DeepMind and incoming assistant professor at Stanford GSB working on AI and economics.

Developer and researcher with public GitHub activity on DeepSeek-AI repositories including DeepSeek-R1 and DeepSeek-VL2, plus coauthor credit on the DeepSeek LLM Technical Report.

Xipeng Qiu is a Fudan University professor whose public work focuses on natural language processing and large language models.

Yusuke Iwasawa is an Assistant Professor in Computer Science at the University of Tokyo whose work spans human-computer interaction and machine learning.

Researcher at Baichuan focused on large language models and multimodal systems. Public publication profiles include work on Baichuan 2, Baichuan-M1, and Baichuan-M2.

Research scientist at DeepSeek and a Ph.D. student in the School of Software at Tsinghua University. His research interests include large language models and multimodal learning.

Tony Gracious completed his PhD in the Department of Computer Science and Automation at IISc Bangalore. His work includes representation learning, temporal point processes, and higher-order interaction forecasting, and he later joined Dolby's Advanced Technology Group in Bangalore.

Jinliang Guo is listed as an author of the NVIDIA technical report Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

Public report authorship links Pengxiang Cheng to the GLM-Z1-Rumination: An Open Frontier-Class Reasoning Model Through Test-Time Scaling at Z.ai.

Public report authorship links Qingyang Ge to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Rudra Murthy is listed as an author of the NVIDIA technical report Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

Co-author of "The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits"; the paper's author notes list Wenhui Wang with Microsoft Research.

Xi Chen is listed as an author of the Z.ai technical report GLM-4.1V-Thinking and GLM-4.5V: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.

Public report authorship links Xinhua Cheng to the GLM-Z1-Rumination: An Open Frontier-Class Reasoning Model Through Test-Time Scaling at Z.ai.

Xuancheng Ren is listed as an author of the Qwen technical report Qwen3 Technical Report.

Public report authorship links Yizhe Yang to the GLM-Z1-Rumination: An Open Frontier-Class Reasoning Model Through Test-Time Scaling at Z.ai.

Public report authorship links Zhongzheng Ren to the GLM-Z1-Rumination: An Open Frontier-Class Reasoning Model Through Test-Time Scaling at Z.ai.

Researcher at OpenAI working on language model training and evaluation, and co-author of the GPT-4 Technical Report.

Research scientist in Tongyi Lab whose official profile highlights post-training, efficient reasoning, and coding large language models.

Qwen researcher and co-lead whose work focuses on pretraining and post-training, multimodal models, agent systems, and large-scale model infrastructure.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Senior research scientist in Tongyi Lab whose official profile highlights post-training, AI for science, evaluation and alignment, multimodal reasoning, and large language model reasoning.

Researcher at DeepSeek-AI in Hangzhou, China and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek contributor and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Ting Song is listed as an author of the BitNet b1.58 2B4T Technical Report; the report states that T. Song is with Microsoft Research.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek contributor and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek contributor and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Co-author of the BitNet b1.58 2B4T Technical Report; the report states Yan Xia is with Microsoft Research.

Researcher at DeepSeek-AI in Hangzhou, China and co-author of the Nature paper introducing DeepSeek-R1.

DeepSeek contributor and coauthor of the DeepSeek-V2 and DeepSeek-V3 technical reports.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Researcher at Moonshot AI and co-author of the Kimi K2.5 report on visual agentic intelligence.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Co-author of GLM-4.1V-Thinking and GLM-4.5V, multimodal reasoning models trained with scalable reinforcement learning.

Researcher affiliated with DeepSeek-AI and co-author of the Nature paper introducing DeepSeek-R1.

Lead Solutions Architect at OpenAI, based in New York City, according to an official OpenAI Forum speaker page.

Co-author of "The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits"; the paper states J. Xue is with Microsoft Research.

Cisco Research researcher working in artificial intelligence and machine learning; current public evidence does not support the prior Google DeepMind profile.

Lead of OLMo, AI2's open-source frontier language models, and Associate Director of the OLMo team at the Allen Institute for AI.

Software engineer publicly identified on OpenAI's GPT-4 contributions page and in a 2023 QCon speaker bio as a Member of Technical Staff on OpenAI's Developer Platform team.

Soumya Batra is a PhD student in computer science at Stanford University and a former research intern at FAIR and Facebook AI Research.

Public report authorship links Ali Payani to the OLMoE: Open Mixture-of-Experts Language Models at Ai2.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Public sources identify Dirk Groeneveld as an OLMo 3 coauthor; a 2022 USC ISI speaker bio described him as a principal engineer at AI2 and technical lead for the AllenNLP Platform team.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Jin Chen is listed as an author of the DeepSeek technical report DeepSeek-V3 Technical Report.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Research scientist at Google DeepMind in Mountain View working on machine learning, reinforcement learning, and robotics.

Research scientist at Meta GenAI in Menlo Park working on foundation models, language generation, and evaluation.

Research scientist at DeepSeek with public scholarly work on large language models and reasoning.

Founder and CEO of Google DeepMind, leading AI research and product development; his work spans AI, neuroscience, game playing, and structural biology.

Research scientist at DeepSeek with a public Google Scholar profile covering large language models and efficient inference.

Research scientist at DeepSeek with public GitHub work on reinforcement learning from human feedback and language models.

Research scientist at DeepSeek with public GitHub work on large language models and AI agents.

Jacob Morrison is a researcher whose work spans language model post-training, alignment, and evaluation. His public research page highlights projects including Tulu 2, Tulu 3, OLMo 2, and RewardBench.

Research scientist at DeepSeek AI working on multimodal large language models and efficient multimodal alignment. Previously completed a PhD at Nanjing University focused on machine learning and computer vision.

Researcher working on speech and multimodal language models, including MiniMax-Speech and related speech understanding work.

Research scientist at DeepSeek with public GitHub work spanning AI systems.

Research scientist at DeepSeek with public GitHub projects on AI systems.

AI scientist at Mistral AI and PhD student at ENS Paris and CNRS. Her research focuses on language grounding, multimodality, and evaluation for multimodal and language models.

Lead of foundation models at MiniMax working on large language models, multimodal pretraining, and efficient training systems. He completed a PhD in computer science at Tsinghua University.

Research scientist at DeepSeek with public GitHub work on language models and AI systems.

Research scientist at Google Research whose public work spans multilingual and large-scale language modeling; arXiv author results include the PaLM paper.

Chief Scientist at Google DeepMind and Vice President of Research leading Gemini, with work spanning scalable sequence learning, large language models, games, and robotics.

Senior research scientist at Ai2 and affiliate associate professor at the University of Washington, with work spanning NLP, machine reading, and reasoning.

Researcher at DeepSeek AI interested in large language models and multimodal language models.

Rohan Anil is a research scientist at Google DeepMind. His public homepage highlights work on large language models, efficient machine learning systems, and multimodal AI.

Researcher affiliated with DeepSeek-AI on Google Scholar and coauthor of the DeepSeek technical reports.

Research scientist at Mistral AI and co-author of the Mistral 7B report.

Researcher and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Vice President of Engineering and Research at Google and site lead for the Google Center in Israel; he also leads Search, Research, and AI for Crisis Response.

DeepSeek researcher and coauthor of the DeepSeek LLM, DeepSeek-V2, and DeepSeek-V3 technical reports.

Research scientist at MiniMax AI Research focused on reinforcement learning, reasoning, multimodal learning, large language models, and large-scale distributed systems. He received a PhD in machine learning from Carnegie Mellon University.

Research scientist at DeepSeek AI and co-author of the DeepSeek-V3, DeepSeek-V2, and DeepSeek LLM technical reports.

Public report authorship links Baobao Chang to the GLM-4.5: Agentic, Reasoning, and Coding Foundation Models at Z.ai.

Chaomin Shen is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Dakun Zhang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Dehao Chen to the PaLM: Scaling Language Modeling with Pathways at Google.

Public report authorship links Dejiang Dou to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Fangrui Zhang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Gianna Lengyel is listed as an author of the Mistral AI technical report Mistral 7B.

Public report authorship links Hang Yan to the GLM-4.5: Agentic, Reasoning, and Coding Foundation Models at Z.ai.

Public report authorship links Haolin Jia to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Haoqi Chen to the GLM-4.5 report at Z.ai.

Researcher at LG AI Research and coauthor of the EXAONE 3.5: Series of Language Models for Real-world Use Cases.

H. Zhang is listed as an author of the DeepSeek technical report DeepSeek-V3 Technical Report.

Public report authorship links Jamie Kiros to the Nemotron-4 340B Technical Report at NVIDIA.

Public report authorship links Jiale Zhi to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Jialiang Wang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Jianfeng Gao to the Nemotron-4 15B Technical Report at NVIDIA.

Public report authorship links Jiangnan Li to the GLM-4.5 report at Z.ai.

Public report authorship links Jian Ma to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Jian Song to the GLM-4.5: Agentic, Reasoning, and Coding Foundation Models at Z.ai.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Jinhui Yang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Researcher at LG AI Research and coauthor of the EXAONE 3.5: Series of Language Models for Real-world Use Cases.

Public report authorship links Kaixin Yang to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Li Dong to the GLM-4.5 report at Z.ai.

Linjie Zhao is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Mahyar Babaei is listed as an author of the Microsoft technical report Phi-4 Technical Report.

Mateusz Litwin is listed as an author of the OpenAI technical report Language Models are Few-Shot Learners.

Ming Ding is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Mingpeng Zhou to the GLM-4.5: Agentic, Reasoning, and Coding Foundation Models at Z.ai.

Public report authorship links Mingxing Zhang to the Gemma 3n Technical Report at Google.

Mingze Li is listed as an author of the Qwen technical report Qwen3 Technical Report.

Researcher at LG AI Research and coauthor of the EXAONE 3.5: Series of Language Models for Real-world Use Cases.

Researcher at Cerebras Systems and coauthor of the Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

Researcher at Salesforce AI Research and coauthor of the XGen-7B Technical Report.

Public report authorship links Peiyi Wang to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Researcher at Salesforce AI Research and coauthor of the XGen-7B Technical Report.

Public report authorship links Qianlin Peng to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Qiao Zhang is listed as an author of the Google technical report PaLM 2 Technical Report.

Qinyuan Wang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Rong Wu to the GLM-4.5 report at Z.ai.

Researcher at LG AI Research and coauthor of the EXAONE 3.5: Series of Language Models for Real-world Use Cases.

Public report authorship links Sebastian Goodman to the Gemma 3n Technical Report at Google.

Public report authorship links Shuai Wang to the GLM-4.5: Agentic, Reasoning, and Coding Foundation Models at Z.ai.

Siyao Huang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Siyuan Fan to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Su Wang to the Gemma 3n Technical Report at Google.

Public report authorship links Tianchu Gao to the GLM-4.5 report at Z.ai.

Trevor Cai is listed as an author of the Google technical report RecurrentGemma: Moving Past Transformers for Efficient Open Language Models.

T. Wang is listed as an author of the DeepSeek technical report DeepSeek-V3 Technical Report.

Public report authorship links Wenbo Bi to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Xiang Li is listed as an author of the MiniMax technical report MiniMax-01: Scaling Foundation Models with Lightning Attention.

Public report authorship links Xiao Liu to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Xiaowei Jiang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Xiaoxin Li to the GLM-4.5 report at Z.ai.

Public report authorship links Xiaoyi Wang to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Xibin Wu to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Xin Fu is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Xuanhao Ge is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Xudong Xie is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Yafei Wen is a MiniMax report-backed author on MiniMax-Text-01, a MiniMax technical report in the LLMpeople catalog.

Public report authorship links Yali Wang to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Yang Jiang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Yibo Tian is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Yifei Lu to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Researcher at Salesforce AI Research and coauthor of the XGen-7B Technical Report.

Yilong Chen is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Yingjie Li to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Yinlong Xu is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Yi Wang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Yong Li is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Researcher at LG AI Research and coauthor of the EXAONE 3.5: Series of Language Models for Real-world Use Cases.

Yuhan Li is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Public report authorship links Yu Liu to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Yuxiang Zhao is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Public report authorship links Yuzeng Li to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Public report authorship links Yu Zhou to the MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention at MiniMax.

Zehui Wu is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Zewen Chi is listed as a co-author of the 2026 arXiv paper "Sparse-BitNet: 1.58-bit LLMs are Naturally Friendly to Semi-Structured Sparsity," with affiliation 1 shown as Microsoft Research.

Public report authorship links Zhang Zhang to the GLM-5: Thinking, Coding, and Agentic Intelligence at Z.ai.

Public report authorship links Zhanhui Kang to the GLM-4.5 report at Z.ai.

Zhengduo Zhuo is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Researcher at Shanghai AI Laboratory and coauthor of the InternLM2 Technical Report.

Zhe Wang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Zhili Liang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Zitong Zhang is listed as an author of the Z.ai technical report GLM-4.5: Agentic, Reasoning, and Coding Foundation Models.

Head of Safety Systems at OpenAI.

Researcher at Databricks and coauthor of the DBRX: A Generalist Open Source LLM.

Researcher at Salesforce AI Research and coauthor of the XGen-7B Technical Report.

Researcher at 01.AI and coauthor of the Yi-Lightning Technical Report.

Researcher at Baichuan and coauthor of the Baichuan 2: Open Large-scale Language Models.

Researcher at Salesforce AI Research and coauthor of the XGen-7B Technical Report.

Researcher at Cerebras Systems and coauthor of the BTLM-3B-8K: 7B Performance in a 3B Model.