Researchers | LLMpeople

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.

Research scientist at Anthropic who leads the Societal Impacts team and works on AI evaluation, alignment, and societal impacts.

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.

Radu Soricut is a Distinguished Scientist at Google DeepMind working on natural language processing and machine learning, with earlier Google Research and Google Translate work.

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.

Tom Henighan works on large language model interpretability at Anthropic. He previously worked on scaling laws at OpenAI and machine learning engineering at Beehive AI, and he studied physics at Stanford after graduating from Ohio State University in 2010 with a degree in English, mathematics, and philosophy.

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.

Aengus Lynch is a fifth-year PhD student in machine learning at Carnegie Mellon University advised by Zico Kolter. His homepage says he works on control, reinforcement learning, games, and machine learning, and his CV shows research internships at Anthropic and Google DeepMind after completing a BASc in engineering physics at the University of British Columbia.

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.

Anand Avati is a PhD candidate at the Stanford AI Lab. His homepage says he is the technical lead of the AI-Enabled ACP project deployed at Stanford Hospital, has served as principal instructor of Stanford's CS229 course, and previously was a distinguished engineer in Red Hat's CTO office after joining through the acquisition of Gluster, where he was a founding engineer and lead architect of GlusterFS.

Andrew Tulloch is a researcher at Meta working on superintelligence and a co-founder of Thinking Machines Lab. His public homepage says he previously worked on machine learning systems at Meta, helped train GPT-4o, GPT-4.5, and o3 at OpenAI, and studied mathematics at the University of Sydney and the University of Cambridge.

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.

Evan Hubinger is Head of Alignment Stress-Testing at Anthropic, where he works on AI safety and alignment. He previously worked at MIRI and OpenAI, studied mathematics and computer science at Harvey Mudd College, and is known for work on inner alignment, deceptive alignment, and alignment stress-testing.

Jacob Hilton is a researcher and executive director at Alignment Research Center, where he works on mechanistic approaches to outperforming random sampling. He previously worked at OpenAI on truthfulness, reinforcement learning, and interpretability for language models, earlier worked at Jane Street, completed a PhD in mathematics at the University of Leeds, and later coauthored Anthropic work on constitutional classifiers.

Ji Lin is a research scientist at OpenAI working on multimodal models, reasoning, and synthetic data. He previously completed his Ph.D. and M.Sc. in EECS at MIT under Song Han, earned a B.Eng. in Electronic Engineering from Tsinghua University, and has interned or worked at Adobe Research, OmniML, and NVIDIA Research.

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.

Luke Zettlemoyer is a professor in the Paul G. Allen School of Computer Science & Engineering at the University of Washington and a Senior Research Director at Meta FAIR. His research focuses on empirical methods for natural language semantics, machine learning for language understanding, and self-supervision for pre-training; he studied at NC State, earned his Ph.D. from MIT, and was a postdoctoral researcher at the University of Edinburgh.

Sanchit Gandhi is a research scientist at Mistral AI. His public Hugging Face and conference speaker profiles say he previously worked on open-source speech technology at Hugging Face and at Apple, helped popularize OpenAI's Whisper ecosystem, and earned a master's degree at the University of Cambridge.

Sandipan Kundu is a member of technical staff at Anthropic. His public The Org profile says he previously held postdoctoral positions at Johns Hopkins and Cornell, worked and studied at the University of Texas at Austin, and earned a master's degree in physics from the Indian Institute of Technology Kanpur.

Sebastian Gehrmann is the head of Responsible AI in the office of the CTO at Bloomberg. His homepage says he previously led Bloomberg's NLP work, earlier researched evaluation of large language models at Google, and earned a PhD from Harvard University. It also highlights research interests in natural language generation, model evaluation, and interpretability.

Sheer El-Showk is a member of technical staff at Anthropic. His public The Org profile says he is also CTO at Lore AI and founder of Nascent AI, previously worked as a senior software engineer at Coiled and held postdoctoral research fellowships at CERN and the CEA, and earned physics and mathematical physics degrees from UC Berkeley and the University of Amsterdam.

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.

CEO of Sand AI. His homepage describes prior work leading multimodal and vision research at BAAI and serving as a senior researcher at Microsoft Research Asia.

Amelie Royer is a research scientist at Kyutai in Paris working on efficient large models and speech-language systems. Before joining Kyutai in June 2024, she spent three years at Qualcomm AI Research working on efficient and multimodal machine learning. She earned a PhD in computer science from ENS Paris-Saclay and LIP6 in 2021 after a master's in applied mathematics from ENS Paris-Saclay.

Ariana Mirian is a senior security researcher at Censys and a PhD student in computer science at UC Berkeley. Her public resume shows earlier AI/ML researcher and data scientist roles at Apple, as well as Stanford degrees in business administration and electrical engineering.

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.

Haotian Zhang is a research scientist on Apple AI/ML's Visual Intelligence team. His homepage says he works on embodied agents that understand the world from 2D and 3D image data as well as natural language, previously interned at Microsoft Research and Azure AI, completed a PhD in electrical and computer engineering at the University of Washington in 2022, and earlier earned master's degrees at Washington and a bachelor's degree at Shanghai Jiao Tong University.

Kartik Sreenivasan is a machine learning researcher whose homepage says he was a final-year PhD student in computer science at the University of Wisconsin-Madison advised by Dimitris Papailiopoulos. The same page says he studies optimization, machine learning, and large-scale distributed settings, earned a B.Tech from the National Institute of Technology Karnataka, worked at Adobe Systems for three years in Bengaluru, and was preparing to join Databricks as a research scientist on the after-training team.

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.

William Saunders is a research scientist at Anthropic working on aligning and evaluating language models. His public homepage says he works at the intersection of game theory, optimization, and deep learning, previously interned at OpenAI, DeepMind, and Mila, studied mathematics at the University of Oxford, and is a PhD student in machine learning at Carnegie Mellon University.

Zhengfeng Lai is an ML Research Scientist at Apple AI/ML. His self-authored CV lists a PhD in Electrical and Computer Engineering from the University of California, Davis, prior Apple internship work, and publications in multimodal and vision-language learning.

Assistant professor at the University of Chicago and head of the Conceptualization Lab, working on language generation, communication, and large language models.

Eric P. Xing is president of Mohamed bin Zayed University of Artificial Intelligence and a professor in Carnegie Mellon University's Machine Learning Department, Language Technologies Institute, and Computer Science Department. His public homepage and biography say his work spans machine learning, statistical methodology, large-scale computational systems, large language models, world and agent models, and biology foundation models; he earned a bachelor's degree from Peking University and PhDs from Rutgers University and the University of Alberta.

Hang Zhu is a Research Scientist at ByteDance Seed focused on LLM infrastructure, including large-scale pre-training and post-training systems.

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.

Marzyeh Ghassemi is the Germeshausen Career Development Professor and an associate professor in electrical engineering and computer science and the Institute for Medical Engineering and Science at MIT, and a CIFAR AI Chair at the Vector Institute. MIT says she joined MIT in July 2021 after serving as an assistant professor at the University of Toronto in computer science and medicine and as a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. MIT also lists a PhD in computer science from MIT, an MSc in biomedical engineering from Oxford University, and bachelor's degrees in computer science and electrical engineering from New Mexico State University.

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.

Renjie Zheng is a researcher at ByteDance. His public OpenReview profile lists prior research experience at Baidu Research and earlier study at Oregon State University and Tongji University, with public work spanning NLP, language models, and reasoning-related research.

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.

Xiangpeng Wei is an algorithm engineer at ByteDance Seed whose public research profile spans large language models, multimodal applications, and multilingual NLP.

Yuwen Xiong is a Research Scientist at ByteDance Seed in the Bay Area. He received a Ph.D. from the University of Toronto's Machine Learning Group and previously worked at Waabi and Uber ATG.

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.

Jifeng Dai is a tenured associate professor in electronic engineering at Tsinghua University and founder of Fundamental Vision. His research spans computer vision, deep learning, multimodal learning, and autonomous driving. He previously worked at Microsoft Research Asia and SenseTime Research, and he received both his bachelor's and PhD degrees from Tsinghua University.

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.

Jifeng Dai is a tenured associate professor in the Department of Electronic Engineering at Tsinghua University. His homepage says his current research focuses on agentic AI and continual learning, and lists prior roles at Shanghai AI Lab, SenseTime Research, and Microsoft Research Asia.

Member of Technical Staff at OpenAI focused on accelerating biomedical intelligence. He was previously a Research Scientist at Google DeepMind.

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.

David Krueger is an assistant professor in robust, reasoning, and responsible AI at the University of Montreal and a core academic member at Mila. His homepage says he trained in deep learning under Yoshua Bengio, Roland Memisevic, and Aaron Courville from 2013 to 2021, was at the University of Cambridge from 2021 to 2024, and founded the nonprofit Evitable in 2025.

Jacob Steinhardt is an Associate Professor of Statistics and EECS at UC Berkeley and the founder and CEO of Transluce, a nonprofit research lab building technology to understand frontier AI systems. He previously spent a postdoctoral year at OpenAI and Open Philanthropy after completing his PhD at Stanford University with Percy Liang, and he coauthored Anthropic interpretability work such as Tracing the thoughts of a large language model.

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.

Neel Nanda is an independent researcher focused on mechanistic interpretability and understanding neural networks. He previously worked on Anthropic's model diffing team, did the ML Alignment & Theory Scholars program, studied mathematics at the University of Cambridge, and is known for interpretability tooling such as TransformerLens.

Xingcheng Yao is a research scientist at Moonshot AI. His public profile notes prior work as a research engineer at Tencent AI Lab, a PhD in computer science from the University of Southern California, and research interests spanning NLP, multimodal systems, and AI agents.

Andy Zou is a final-year PhD student in the Language Technologies Institute at Carnegie Mellon University. His homepage says he studies large language models, reasoning, coding, and AI safety, and his CV shows previous internships at Scale AI and Google after BS and MS degrees in electrical engineering and computer sciences from UC Berkeley.

Carl Vondrick is an Assistant Professor of Computer Science at Columbia University and a researcher at Apple whose work spans computer vision, machine learning, and multimodal systems. He previously worked as a research scientist at Google and a visiting researcher at Cruise, completed his PhD at MIT in 2017 after a BS at UC Irvine, and coauthored Anthropic interpretability work such as Tracing the thoughts of a large language model.

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.

Xinyi Chen is a PhD candidate in computer science at Princeton University and concurrently a research scientist at Google DeepMind. Her public homepage says she works at the intersection of machine learning, optimization, and dynamical systems, focusing on robust and efficient methods for sequential decision-making and control, and that she previously completed undergraduate studies in mathematics at Princeton.

PhD student in computer science at Peking University and research intern at PACMAN whose public homepage highlights computer systems, compilation, and parallel optimization for AI applications.

Assistant professor at Columbia University working on embodied AI, robot learning, world models, and computer vision. Previously a research scientist at Google DeepMind.

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.

Sanjiv Kumar is a Google Fellow and vice president at Google DeepMind. His homepage says he leads a machine learning team working on foundation models including LLMs and generative AI for Gemini, has also led research in deep retrieval and ranking, and earned a Ph.D. in computer science from Carnegie Mellon University in 2005.

Chao Zhang is an applied scientist in the Alibaba Foundation Model team. His public profile notes a PhD in computer science from the University of Illinois Urbana-Champaign and research interests in NLP, large language models, reasoning, and multimodal generation.

Shekoofeh Azizi is a staff research scientist and research lead at Google DeepMind. Her Google Research profile says she works on biomedical super-intelligence to accelerate scientific discovery, with a particular focus on cancer, and helps lead efforts behind Med-PaLM, Med-Gemini, TxGemma, Tx-LLM, and C2S-Scale. UBC's Centre for Internet Computing profile says she earned a bachelor's degree in electrical engineering from Sharif University of Technology and a PhD in computer science from the University of British Columbia.

Yacine Jernite leads the ML and Society team at Hugging Face. His personal site says he works on ML systems governance at the intersection of regulatory and technical tools, with a focus on NLP models, data curation, documentation, and governance, and that he completed a Ph.D. in computer science at New York University under David Sontag.

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.

Ke Ye is a fifth-year PhD student in the Language Technologies Institute at Carnegie Mellon University. His homepage says his research spans natural language processing, machine learning, and artificial intelligence, including language models, speech and speech-language models, conversational AI, and reasoning, and notes that before Carnegie Mellon he worked at Apple Intelligence. His OpenReview profile lists Apple foundation-model work alongside earlier roles at Google, Roblox, and Capital One.

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.

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.

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

Aakanksha Chowdhery is an adjunct professor at Stanford and a researcher at Reflection AI working on agentic LLMs and reinforcement learning for self-improving agents. Her homepage says she previously led work on the 540B PaLM model and Gemini at Google, earlier led interdisciplinary research initiatives at Microsoft Research and Princeton University, and completed a PhD in electrical engineering at Stanford University.

Kanishka Rao is a researcher at Google. Public Google Research and OpenReview profiles connect Kanishka Rao to work in natural language processing, speech processing, robotics, and responsible AI, and list earlier student-research and internship roles at Carnegie Mellon University, Google Research, and Microsoft Research along with a master's degree in language technologies from Carnegie Mellon University.

Ksenia Konyushkova is a research scientist at Google DeepMind in London working on computer vision, embodied AI, and reinforcement learning. Her personal homepage describes earlier roles at Google Research in Zurich and postdoctoral work after EPFL.

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.

Zhengyuan Liu is a research scientist at Alibaba Group and a PhD student at the National University of Singapore. His public profile highlights work in natural language processing, vision-language models, and grounding.

Cem Anil is a research scientist at Anthropic and part of the company's Alignment Science team. His homepage says he recently completed a PhD at the University of Toronto and Vector Institute supervised by Roger Grosse and Geoffrey Hinton. He studies the intersection of deep learning and AI safety, especially robustness and generalization in large language models and scaling laws for dangerous capabilities.

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.

John Canny is the Paul and Stacy Jacobs Distinguished Professor of Engineering at UC Berkeley. His Berkeley faculty homepage shows he taught CS188: Introduction to Artificial Intelligence in Spring 2025. An official Berkeley EECS news profile says he joined the Berkeley faculty in 1987 and earned bachelor's degrees in computer science and theoretical physics and electrical engineering from Adelaide University, followed by master's and PhD degrees from MIT, with contributions spanning AI, robotics, computer graphics, human-computer interaction, computer security, computational algebra, and computational geometry.

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.

Zhen Ye is a researcher in the Qwen team at Alibaba Cloud. His public profile notes a PhD in computer science from the University of Massachusetts Amherst and research interests in natural language understanding, generation, and reasoning.

Marina Danilevsky is a research staff member at IBM Research working on NLP, human-centered AI, foundation models, and data-centric AI. She has been at IBM since 2014 and has led work on ontology learning, data quality, and model evaluation. She earned her PhD in Informatics from the University of Edinburgh.

Postdoctoral associate at MIT CSAIL working at the intersection of machine learning and healthcare. He earned a PhD in computer science from Cornell University and studies multimodal medical AI.

Technical staff member on Moonshot AI's agent team whose public OpenReview profile lists work across deep learning, natural language processing, large language models, vision-language models, and agents.

Researcher at Anthropic whose public report authorships and scholarly profiles cover language model evaluation, AI safety, and robustness.

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.

Feida Zhu is a ByteDance researcher in computer vision. Public sources show prior roles at Tencent Youtu Lab and Nanyang Technological University, and a PhD in Computer Science from The University of Hong Kong.

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.

Pengyu Cheng is a researcher at Alibaba Group leading reinforcement-learning training for the Qwen large-model application team. His homepage also lists prior work with Moonshot AI and Tencent's Hunyuan large-model team.

Computer scientist and Turing Award laureate known for foundational work in deep learning and computer vision; 2025-2026 public sources describe him as founder and executive chairman of Advanced Machine Intelligence Labs and a professor at NYU.

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.

Yong Shan is a ByteDance researcher whose public profiles and publication record indicate work across LLMs, neural machine translation, dialogue systems, and music generation.

Founder and CEO of Ricursive Intelligence, a frontier AI lab targeting chip design; previously a Senior Staff Research Scientist at Google DeepMind and an early employee at Anthropic.

Public sources identify Can Huang as a ByteDance researcher. OpenReview lists prior research work at Intsig Information Co. Ltd., master's study at Shanghai Jiao Tong University, and undergraduate study at Xi'an Jiaotong University.

Weihao Yu is a researcher in computer vision, multimodal AI, and neural architecture design. Public profiles show PhD and postdoctoral work at the National University of Singapore, a 2025 Research Scientist role at ByteDance Seed, and a 2026 appointment at Peking University Shenzhen Graduate School.

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.

Luca Soldaini

Daya Guo

Amanda Askell

Deep Ganguli

Baosong Yang

Mona Jalal

Radu Soricut

Yuxiang Zheng

Ming-Yu Liu

Xinyun Chen

Xueyan Zou

Arash Vahdat

Haoyu Lu

Hyung Won Chung

Tom Henighan

Dilek Hakkani-Tur

Jialong Tang

Xinyu Zhang

Aengus Lynch

Alexandre Ramé

Anand Avati

Andrew Tulloch

Benyou Wang

Brian Lester

Evan Hubinger

Jacob Hilton

Ji Lin

Kartikeya Mangalam

Luke Zettlemoyer

Sanchit Gandhi

Sandipan Kundu

Sebastian Gehrmann

Sheer El-Showk

Wanli Ouyang

Yue Cao

Amelie Royer

Ariana Mirian

Ashvin Nair

Haotian Zhang

Kartik Sreenivasan

Matei Zaharia

Tulsee Doshi

William Saunders

Zhengfeng Lai

Ari Holtzman

Eric P. Xing

Hang Zhu

Jason Phang

Juntang Zhuang

Marzyeh Ghassemi

Minhao Cheng

Renjie Zheng

Sang Michael Xie

Sarath Chandar

Tim Brooks

Tong Wu

Utku Evci

Xiangpeng Wei

Yuwen Xiong

David Mély

Jifeng Dai

Joost Huizinga

David Brandfonbrener

Junyang Lin

Jifeng Dai

Khaled Saab

Chinmay Hegde

David Krueger

Jacob Steinhardt

Jason Yosinski

Neel Nanda

Xingcheng Yao

Andy Zou

Carl Vondrick

Kelvin Guu

Xinyi Chen

Jiuzheng Wang

Yunzhu Li

Jean-Baptiste Alayrac

Le Yu