Reasoning Models | Field

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.

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.

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.

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.

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

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.

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.

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.

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.

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

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 OpenAI whose public profiles describe work on generative AI and reinforcement learning, after PhD study at the University of Cambridge.

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.

Jian-Hui Duan is an algorithm researcher in the ByteDance Seed LLM team whose public homepage highlights work on pretraining data, training optimization, and distribution-shift mitigation for large language models.

Public profiles and publication indexes link Xingyan Bin to ByteDance research work and Tsinghua University, with papers in recommendation, retrieval, MoE models, and LLM pre-training/quantization.

Zhiqi Lin is publicly listed on OpenReview as a researcher at ByteDance Inc. OpenReview also lists prior computer science study at the University of Science and Technology of China, with undergraduate study from 2015 to 2019 and PhD study from 2019 to 2024.

Zihan Liu's public homepage describes him as a senior research scientist at NVIDIA ADLR working on LLM reasoning, post-training, and retrieval-augmented generation.

Mistral AI's company page identifies Guillaume Lample as a co-founder. His public GitHub profile describes research on unsupervised machine translation, symbolic mathematics, and theorem proving.

Guanghan Ning is a ByteDance researcher whose public homepage says he switched to foundation models at the beginning of 2023, especially code LLMs, after earlier work in computer vision and deep learning.

Qi Liu is a ByteDance researcher whose public OpenReview profile lists prior research work at Horizon Robotics and studies at Fudan University and Huazhong University of Science and Technology. Public expertise areas include multimodal large language models, gesture recognition, metric learning, and deep learning.

Qiyang Min is a researcher at ByteDance Inc. whose public profiles and publication record indicate work on large language models, memory-augmented architectures, and related model systems. OpenReview lists prior research experience at Baidu and undergraduate study in software engineering at Nanjing University.

Chenwei Lou is a researcher at ByteDance Seed. Public profiles indicate earlier research experience at Tencent, an MS period at Harbin Institute of Technology, and earlier undergraduate study at Jilin University.

Abhinav Khattar is a research scientist at NVIDIA working on LLM alignment, customization, and machine translation. Before joining NVIDIA, he earned a master's degree in computer science from Carnegie Mellon University and worked on information retrieval and speech recognition.

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.

Research scientist at ByteDance Seed and final-year PhD student at the University of Toronto.

Jiangjie Chen is a researcher at ByteDance Seed. He earned a Ph.D. in computer science from Fudan University in 2024 and works on reasoning models, autonomous agents, and machine reasoning.

Qiying Yu is a PhD student at the Institute for AI Industry Research (AIR), Tsinghua University, working on self-supervised learning and multimodal large models.

Yongfei Liu is a researcher whose public profiles list interests in CodeLLM, generative multimodality, and vision-language research. His homepage says he completed a joint PhD program at the University of Chinese Academy of Sciences and ShanghaiTech University in 2022 after a bachelor's degree from Xidian University in 2017.

Ziheng Jiang is an AI researcher working on large language models and machine learning systems. His public homepage says he is a Principal AI Researcher at Meta and previously was a Principal Research Scientist at ByteDance.

Haobin Jiang is a Peking University PhD student whose public profiles describe research in reinforcement learning, robotics, and LLM post-training.

Qingping Yang / 杨清平 is a researcher whose public homepage highlights work on LLMs, especially code generation, table understanding, and structured information extraction. Public sources also connect him to earlier table understanding publications and recent reinforcement-learning-for-LLMs work.

Siyu Yuan is a final-year Ph.D. student at Fudan University advised by Deqing Yang and Yanghua Xiao, working on reasoning models and autonomous agents.

Weinan Dai is a PhD student in Computer Science and Technology at Tsinghua University. Public profiles and publications link him to research on large language models, reasoning, and reinforcement learning, including Seed1.5-Thinking, DAPO, MemAgent, and Enigmata.

OpenReview lists Grace Lam as a researcher at NVIDIA after prior work at Google, with study at Stanford and MIT. NVIDIA public pages connect her to Cosmos Policy for robot control and Nemotron-Cascade 2 for LLM post-training.

Aleksandra Piktus is a research scientist at Mistral AI. Her public speaker profiles say she works on multilinguality, representation learning, and responsible AI, and previously worked at the University of Cambridge on multimodal representation learning and cross-lingual transfer, where she completed a PhD.

Boxin Wang is a senior research scientist at NVIDIA working on practical and scalable large language models, including trustworthiness, multimodal language modeling, and retrieval-augmented generation. He earned a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign.

Public sources associate Zewei Sun with ByteDance and list Nanjing University education (BS 2013-2017, MS 2017-2020), with research spanning machine translation and later large language model work.

Ning Dai is a PhD student in EECS at Oregon State University. His public OpenReview profile includes ByteDance Seed's Seed1.5-Thinking report and lists expertise in code generation, post-training for LLMs, and RNA design.

Yao Luo is an LLM researcher at the ByteDance Seed Team. Her public homepage lists research interests in sparse architectures, linear attention, long-context modeling, and model merging.

Yufeng Yuan is listed on OpenReview as staff at ByteDance Seed, previously at Tencent AI Lab, with an MS in Computing Science from the University of Alberta.

Zhuolin Yang's personal page says he is a Research Scientist at NVIDIA ADLR whose interests include trustworthy machine learning, multimodal LLMs, and reasoning.

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.

Public OpenReview profile lists Ning Wu as a researcher at ByteDance after prior research work at Microsoft and an MS at Beijing University of Aeronautics and Astronautics (2018-2021). Publications on that profile cover NLP, cross-lingual dense retrieval, recommendation systems, and large language model evaluation.

Qianyu He is a PhD candidate in Computer Science at Fudan University whose work focuses on large language model reasoning and instruction following. Her public homepage lists a research internship at ByteDance Seed-LLM-Horizon and names Seed1.5-Thinking among her projects.

Ahmed H. Awadallah is a Partner Research Manager at Microsoft Research. His work spans large language models, search, conversational AI, and applied machine learning.

Kaihua Jiang is publicly associated with ByteDance Seed report authorship. An OpenReview profile for Jiang Kaihua lists a confirmed @bytedance.com email, links to the GitHub account jiangkaihua, and shows current PhD study at the University of Chinese Academy of Sciences since 2024.

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.

Public profile information identifies Kai Hua as a researcher at ByteDance Seed with prior research experience at Kuaishou MMU and a master's background in EECS at Peking University. His listed research areas include deep learning, NLP, language modeling, and multimodal AI.

Bairen Yi is a researcher at ByteDance's Seed Foundation Team. Public publication records link him to work on efficient LLM inference, KV-cache compression, and model/model-expert merging.

Yangyi Chen is a research scientist at NVIDIA. His homepage says he works on LLM post-training and LLM-based coding agents, and it lists him as a Nemotron-Cascade 2 coauthor.

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.

Alex Ficek is a final-year PhD student at the University of Michigan and incoming applied scientist at Microsoft working on language models, agents, reinforcement learning, and infrastructure.

Defa Zhu is an AI researcher whose public homepage says his work focuses on large language models and stronger model architectures.

Public OpenReview and DBLP profiles associate Chen Dun with research in large language models, federated learning, distributed deep learning, and graph neural networks.

Public sources attribute Wenchang Ma to publications at EMNLP 2021, ICLR 2023, WWW 2024, and ACM TOIS 2024. OpenReview lists prior study at Tsinghua University and the National University of Singapore.

Xunhao Lai is a master's student at Peking University working on natural language processing and large language models, with a focus on long-context modeling and efficient attention.

Public sources identify Yiyuan Ma as a researcher whose OpenReview profile lists ByteDance roles in machine learning and large language models, following MS study in communication at Beijing University of Posts and Telecommunications.

Lin Yan is a ByteDance Seed researcher whose public OpenReview profile lists expertise in NLP and LLMs, with earlier work in recommender systems.

Public OpenReview information identifies Sijun Zhang as a researcher formerly at ByteDance and later at WeChat AI, Tencent, with listed publications on mixture-of-experts methods and transformer training stability.

Public profiles on OpenReview and DBLP link Wenlei Shi to Microsoft Research (2019-2024) and publications in PDE learning, scientific machine learning, code generation, and reasoning-related LLM work.

Publicly listed as a ByteDance researcher focused on large language models, with Tsinghua University education history, and as an author on ByteDance Seed's Seed1.5-VL and Seed1.5-Thinking reports.

Jiazhan Feng is a Research Scientist at ByteDance Seed. Public profiles describe his research around multimodal agents, large language models, and dialogue systems, and list prior PhD training at Peking University with a visiting student period at the University of Oxford.

Kang Liu is a ByteDance researcher whose public OpenReview profile lists prior MS study at Wuhan University. His recent public publications focus on LLM reasoning, long-context methods, and tool-use reinforcement learning.

Thomas Scialom is a research scientist at Meta in Paris working on large language models, post-training, and agents.

Tianyang Zhan is a researcher at ByteDance. Publicly listed publications connect him to ByteDance Seed work on large language model reasoning and evaluation, including Seed1.5-Thinking and SuperGPQA.

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.

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.

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).

Yuhua Jiang is a PhD student in the Department of Automation at Tsinghua University, advised by Qianchuan Zhao, whose public profile focuses on reinforcement learning and recent LLM-related RL methods.

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.

Researcher and engineer whose public work focuses on large language models, reasoning systems, and open-source machine learning.

Haibin Lin works on LLM infrastructure at ByteDance Seed, focusing on training systems for large language and multimodal models from pre-training to post-training.

Chengzhi Wei is credited on the Seed1.5-VL and Seed1.5-Thinking technical reports. An OpenReview profile under the reordered name 'Wei Chengzhi' lists a ByteDance researcher role starting in 2023 and MS study at the University of California, Los Angeles from 2020 to 2022.

Public sources identify Feng He as a ByteDance researcher; OpenReview lists earlier MS study at Sichuan University and expertise in video retrieval.

Lihua Qian is a ByteDance researcher whose public OpenReview and DBLP profiles show work in text generation, diffusion models, and non-autoregressive machine translation.

Wenliang Dai's homepage identifies him as a research scientist at NVIDIA. OpenReview lists prior study at HKUST, University College London, and the University of Nottingham.

Yantao Du is a researcher at Seed, ByteDance. Public sources link earlier work in dependency parsing with more recent large language model research.

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.

Rahul Gupta's homepage describes him as a senior applied science manager at Amazon Nova whose work spans speech, language, and multimodal AI.

Yifan Sun is a computer vision and graphics researcher whose public homepage lists interests in computer graphics, computer vision, joint data analysis, and machine learning.

Public OpenReview and personal homepage/blog for Wei Shen show work on reinforcement learning from human feedback, adaptive chain-of-thought control, long-context behavior, and LLM data-scaling analysis.

Public DBLP and OpenReview profiles link Yuqiao Xian to work on person re-identification, adversarial attacks, long-tailed recognition, and pre-training data selection. OpenReview lists ByteDance career history from 2022 to 2025.

Zhiruo Wang is a principal researcher at Microsoft working on efficient, effective, and responsible natural language intelligence. His homepage says he received a PhD in Computer Science from Yale University in 2024.

Hongli Yu is a PhD student at the Institute for AI Industry Research, Tsinghua University. Public records also show prior undergraduate study in Computer Science and Technology at Harbin Institute of Technology and authorship on the ByteDance Seed report Seed1.5-Thinking.

Public OpenReview and DBLP records link Ruofei Zhu to 2025 ByteDance reinforcement-learning work on LLMs, including DAPO, VAPO, and Seed1.5-Thinking. OpenReview also lists an MS in Software Engineering from Peking University.

Ya Wang is publicly listed as affiliated with ByteDance Seed in Beijing. A disambiguated dblp profile also lists prior affiliation with Tencent's Machine Learning Platform Department and a PhD completed in 2021 at Peking University's School of Mathematical Sciences (LMAM).

Public OpenReview records list Bohong Wu as an MS student at Shanghai Jiao Tong University starting in 2020, with confirmed sjtu.edu.cn and bytedance.com emails and expertise in natural language processing, multimodality, and multilingual research.

Public OpenReview information identifies Guanlin Liu as a ByteDance researcher with listed expertise in large language models, reinforcement learning, and adversarial machine learning. The same profile lists prior study at the University of California, Davis and Zhejiang University.

AI researcher and engineering leader at OpenAI working on multimedia, generation, reasoning, and representation learning. His public work focuses on maximizing the benefits of AI while minimizing harms.

Assistant professor at UC Berkeley whose public profiles focus on speech interfaces, speech synthesis, and language grounding.

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

Joshua Batson leads a team at Anthropic focused on mechanistic interpretability. MIT's SDSCon speaker page also notes earlier work on viral genomics and computational microscopy at the Chan Zuckerberg Biohub and an MIT Ph.D. in pure mathematics.

NVIDIA identifies Mohammad Shoeybi as a senior research scientist who manages the NLP team within its Applied Deep Learning Research group; the same profile states he received a PhD from Stanford University in 2010.

Public NVIDIA and HKUST sources identify Renjie Pi as a researcher in multimodal learning and large language models.

Tingting Ma is publicly listed on OpenReview as a researcher at ByteDance Inc. and a former PhD student at Huaihai Institute of Technology, with expertise in large language models and low-resource NLP.

Machine learning researcher and Columbia PhD student working on NLP, diffusion models, reinforcement learning, and applied probability; contributed to OpenAI reasoning-model system-card work.

Member of technical staff at OpenAI focused on code generation and synthetic data for post-training, with interests in coding, reasoning, human data, reinforcement learning, and self-improving systems.

Research scientist at OpenAI focused on large language models, post-training, reasoning, and evaluation; previously completed a PhD at NYU.

Founder of REWORKd and an applied AI engineer previously at OpenAI, Scale AI, and Stanford research, with work spanning autonomous agents and LLM applications.

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.

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

Chenguang Xi is publicly listed as an author on ByteDance Seed's Seed1.5-Thinking report. A matching OpenReview profile shows a confirmed @bytedance.com email, PhD study at Tufts University from 2010 to 2017, and undergraduate study at Shanghai Jiao Tong University from 2006 to 2010.

Chenxiao Liu is an MS student at Peking University whose public OpenReview profile lists publications in code intelligence, source-code QA, and LLM evaluation, including collaboration with ByteDance researchers on EvaLearn.

Public sources identify Liangqiang Chen as a researcher at ByteDance AI Foundation. His OpenReview profile lists a confirmed @bytedance.com email and links to the GitHub account chenup; he is also listed as an author on the Seed1.5-VL and Seed1.5-Thinking technical reports.

Qi Hou is a researcher at AML, ByteDance Inc. Public OpenReview information also lists prior MS study in Electronic Engineering at Tsinghua University.

Public sources identify this Wenqi Wang as a ByteDance researcher and a former M.S. student at Peking University (2021-2024) with NLP expertise.

Public sources identify Xuwu Wang as a researcher working on entity linking, with a 2018-2023 PhD-student history at Fudan University and publications on multimodal entity linking and knowledge graphs.

OpenReview lists Yuntao Li as a Researcher at ByteDance Inc. and a PhD student at Peking University from 2017 to 2022.

Alexandre Rame is a research scientist at Mistral AI working on post-training, evaluation, and reasoning for large language models.

Barry Haddow is a natural language processing researcher affiliated with Microsoft Research and the University of Edinburgh.

Postdoctoral researcher at Stanford Graduate School of Business studying how humans and AI learn from experience and language, and also working on AI training at OpenAI.

Senior AI scientist at the Technology Innovation Institute and adjunct assistant professor at MBZUAI, working on multimodal foundation models, vision-language learning, and 3D generation.

Siyao Liu is a researcher at ByteDance Seed. A public OpenReview profile lists career history at Seed, ByteDance Inc. from 2020 to present and publications on competitive programming test generation and multilingual software engineering benchmarks.

Ru Zhang is a researcher publicly linked to ByteDance through technical-report authorship and an OpenReview profile with a confirmed @bytedance.com email.

Publicly listed on dblp as Xiaoying Jia 0005 with affiliation ByteDance and an attached ORCID, with 2025 publications on high-performance LLM serving, model merging in LLM pre-training, and Seed Diffusion; also listed as an author on the Seed1.5-VL and Seed1.5-Thinking technical reports.

Public profiles identify Xintong Hao as a researcher at ByteDance Inc. OpenReview lists expertise in deep learning and search relevance, and the linked GitHub profile places the account in Beijing, China.

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.

Tao Sun is a ByteDance-affiliated researcher listed on the Seed1.5-Thinking report and on DBLP with 2025 publications in cross-lingual chain-of-thought reasoning, multilingual form parsing, and multilingual code evaluation.

Publicly listed on OpenReview as a researcher at ByteDance. He is an author on Seed1.5-Thinking and OpenReview-listed ByteDance papers including DAPO and Model Merging in Pre-training of Large Language Models.

Chi Zhang is a ByteDance Seed-affiliated research author whose public publication record spans RLHF and LLM post-training systems, alongside earlier reinforcement learning work.

Haojie Pan is a coauthor of ByteDance Seed's Seed1.5-Thinking report on arXiv. Public records on DBLP and GitHub also attribute earlier work under this name in commonsense knowledge graphs, conversational search, multi-review summarization, and the Kuaipedia multimodal encyclopedia project.

Public evidence links Liang Hu to ByteDance Seed through the Seed1.5-Thinking author list and as a corresponding author of FINSEARCHCOMP, a financial search and reasoning benchmark paper for LLM agents.

Public records on DBLP attribute Zhuolin Zheng to publications spanning intelligent video surveillance (2018), time-of-flight depth imaging (2021), network abnormal detection (2025), and ByteDance LLM infrastructure (2025).

Jiafan He's public homepage identifies him as a UCLA PhD student advised by Quanquan Gu, with research focused on machine learning, reinforcement learning, and optimization.

Lingjun Liu is publicly listed on OpenReview as a researcher at Seed, ByteDance Inc., with an MS in Computing from Imperial College London.

Alexander Bukharin is an applied research scientist at NVIDIA working on large language models, with public NVIDIA materials highlighting reinforcement learning and model robustness.

NVIDIA's public author page identifies Chankyu Lee as a research scientist on the Applied Deep Learning research team, focusing on NeMo LLMs and retrieval-augmented generation. NVIDIA public report pages also list him as a coauthor of Nemotron-Cascade.

Member of technical staff at OpenAI working on reasoning, reinforcement learning, and post-training.

Jeff Tworek is a researcher at OpenAI working on GPT-4.1. Before joining OpenAI in 2022, his public profile notes work on image generation, robotics, reinforcement learning, and POMDPs.

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.

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.

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.

Jingjing Xu is publicly linked to ByteDance through a confirmed bytedance.com OpenReview profile and ByteDance Seed publication pages, and is listed as an author on Seed-Thinking-v1.5 and Let the Code LLM Edit Itself When You Edit the Code.

Taiqing Wang has a public DBLP profile with 2023 papers on recommendation systems, including work on graph neural networks and data subsampling. The provided arXiv report also lists Taiqing Wang among the ByteDance Seed authors of Seed1.5-Thinking.

Baoquan Zhong is publicly listed as an MS student at Zhejiang University. He appears as a coauthor on ByteDance Seed's Seed1.5-Thinking arXiv report and on the OpenReview paper ReTool.

Dongfu Jiang is a Ph.D. student at the University of Waterloo affiliated with the Vector Institute and TIGER Lab. His homepage lists research interests in LLM and VLM post-training, multimodal evaluation, and agentic tool-use systems.

Cheng Ren is publicly listed on OpenReview as a software engineer at Seed, ByteDance Inc. and a Brown University MS alum. He is also credited as an author on ByteDance Seed's Seed1.5-Thinking report.

Public OpenReview information lists Ke Shen as a researcher at Seed, ByteDance Inc. with expertise in language models, pretraining, and information retrieval.

Shipeng Yan is a co-author on ByteDance Seed's Seed1.5-Thinking and Seed1.5-VL technical reports. DBLP records additional publications on large-scale LLM training, self-rewarding preference optimization, and continual vision-language pretraining.

Shuangzhi Wu is listed as an author on ByteDance Seed technical reports and has a public DBLP publication record spanning NLP topics including machine translation, summarization, translation quality estimation, and related language modeling work.

Wanjun Zhong is a researcher in large language models whose public bibliography includes work on AGIEval, MemoryBank, tool-use benchmarking, knowledge editing, and code-generation reliability. Zhong is also listed as a coauthor on the Seed1.5-VL and Seed1.5-Thinking technical reports.

Zuquan Song is publicly listed as a ByteDance Seed author on Seed technical reports and on ByteDance Seed's OSDI 2025 publication "Understanding Stragglers in Large Model Training Using What-if Analysis." dblp also attributes 2024-2025 publications on LLM training infrastructure, checkpointing, faulty-machine detection, and GPU communication overlap to Zuquan Song.

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

Borui Wan is a Ph.D. student at the University of Hong Kong, listed on Chuan Wu's team page as starting in 2022. He is the lead author of the USENIX NSDI 2025 paper "ByteCheckpoint: A Unified Checkpointing System for Large Foundation Model Development" and is also listed as an author on the ByteDance Seed report "Seed1.5-Thinking."

Public sources connect Chengquan Jiang to ByteDance Seed and related publications on mixture-of-experts systems, LLM tool use, speculative decoding, and efficient LLM serving. A DBLP author profile lists papers from 2022 to 2025 including ByteTransformer, FLUX, COMET, ReTool, SwiftSpec, and LiquidGEMM.

Public sources identify Guangming Sheng as a coauthor of Seed1.5-Thinking and HybridFlow, with DBLP-listed publications including MSPipe (KDD 2024), HybridFlow (EuroSys 2025), and Robust LLM Training Infrastructure at ByteDance (SOSP 2025).

Jiecao Chen is publicly listed as an author under ByteDance Seed on the Seed1.5-Thinking arXiv report. A DBLP profile for Jiecao Chen also lists 2025 publications including ToolHop and Recitation over Reasoning, indicating work on large language models, multi-hop tool use, and reasoning evaluation.

Kaiyuan Chen is a researcher at ByteDance Seed. Public sources also list him as a former MS student in the School of Software at Tsinghua University and index his ICML 2024 paper CogDPM.

Author on ByteDance Seed's Seed1.5-Thinking report; public publication record under the same name spans distributed systems, GPU services, and dynamic neural network optimization.

Publicly attributable DBLP records list Shengxian Wan on information retrieval and recommender-systems publications from 2011 to 2019, including SIGIR, AAAI, and IJCAI papers. Shengxian Wan is also listed as an author on ByteDance Seed's Seed1.5-Thinking report.

Ting-Han Fan has a public dblp publication record spanning 2023-2025, including work on transformer length extrapolation, regular language reasoning, and long-context reasoning benchmarks, and is listed as an author on ByteDance Seed's Seed1.5-Thinking report.

Publicly listed as a coauthor of ByteDance Seed's Seed1.5-Thinking report. A DBLP profile under the same name also lists 2025 papers on multi-hop tool use benchmarking and long-context reasoning.

Xiaoran Jin is publicly listed as an author on ByteDance Seed's Seed1.5-Thinking report and the official Seed-Prover publication page, and is linked to the GitHub contributor account xiaoranjin-bd from the official ByteDance-Seed Seed-Prover repository.

Xinnian Liang is publicly listed as a coauthor of ByteDance Seed's 2025 arXiv report Seed1.5-Thinking. An exact-name DBLP author page shows publications from 2020 onward in natural language processing, including summarization, retrieval, multilingual and multimodal modeling, and translation-related work.

Public sources identify Zhengyin Du as a ByteDance Seed report and paper coauthor, with a dblp author profile listing 2024-2025 publications on tool use, multi-hop tool use, and reasoning benchmarks.

Jianpeng Jiao is listed on a public ByteDance Seed paper and on ByteDance Seed technical reports, linking Jiao to language-model and retrieval-oriented research at ByteDance Seed.

AI Scientist & Observability Lead at Mistral AI.

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.

Public NVIDIA sources identify Bryan Catanzaro as Vice President of Applied Deep Learning Research and maintain a research profile page for him.

Publicly listed on OpenReview as Tao Peng, with a publication on compositional reasoning evaluation of large language models and a reported PhD-student history in Tsinghua University's Department of Automation.

Public sources identify Tiantian Fan as a researcher at ByteDance Seed on OpenReview and as a co-author on ByteDance Seed's Seed-Thinking-v1.5 and DAPO publications.

Marcin Michalski is a researcher at Microsoft whose public profile and Google Scholar page highlight work on small language models, reasoning, and machine learning systems.

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.

Rudra Murthy 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 Xinhua Cheng to the GLM-Z1-Rumination: An Open Frontier-Class Reasoning Model Through Test-Time Scaling at Z.ai.

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

Publicly available Moonshot AI technical reports list Zheng Zhang as a coauthor on Kimi-VL and Kimi K2. The surviving public evidence supports research authorship on language and multimodal systems, not a separately verified individual employer profile.

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

Jiaze Chen is publicly listed as a coauthor on ByteDance Seed's 2025 Seed-Thinking-v1.5 publication, the Seed1.5-VL technical report, and the Seed-Coder repository/report, indicating contributions across reasoning, vision-language, and code-focused foundation model work.

ByteDance Seed publicly identified Liang Xiang in December 2024 as Head of the Doubao Foundation Model Team. Public Seed and DBLP records also list him as a coauthor on work about LLM pre-training model merging and ByteDance LLM training infrastructure.

Public OpenReview profile information identifies Wenyuan Xu as a researcher at Seed, ByteDance Inc. and shows a confirmed @bytedance.com email. The profile is also connected to ByteDance Seed-authored work, including the Seed1.5-Thinking report and a MATH-AI 2025 submission.

Guang Shi is publicly listed as a coauthor on ByteDance Seed papers including Seed1.5-VL Technical Report, Seed1.5-Thinking, Emerging Properties in Unified Multimodal Pretraining, and UI-TARS, supporting a conservative profile centered on vision-language models, multimodal pretraining, and GUI agents.

Shen Yan is publicly listed as a co-author on ByteDance Seed research publications including Seed1.5-VL, Seed1.5-Thinking, MME-CoT, and TC-MoE.

Public sources list Yanghua Peng as a coauthor on ByteDance Seed technical reports and on ByteDance engineering research artifacts related to distributed training and checkpointing for large models.

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

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

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

Researcher at IBM Research and coauthor of the Scaling Granite Code Models to 128K Context.

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical reports.

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

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

Publicly listed as Jing Su on ByteDance Seed publications including Seed1.5-Thinking (2025), Seed Diffusion (2025), and The Rise and Down of Babel Tower (2025), indicating research involvement across reasoning models, diffusion language models, and multilingual code LLMs.

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

Jyoti Aneja is a report-backed author in the LLMpeople atlas, connected through Textbooks Are All You Need.

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

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

Saurabh Kumar is listed as an author of the Microsoft technical report Phi-4-mini-reasoning: Exploring the Limits of Small Reasoning Language Models in Math.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical reports.

Researcher at Qwen and coauthor of the Qwen-Image-2.0 Technical Report.

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical reports.

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

Yuchen Liu is listed as an author of the Microsoft technical report Phi-4-mini-reasoning: Exploring the Limits of Small Reasoning Language Models in Math.

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

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

Researcher at Baidu and coauthor of the ERNIE 4.5 Technical Report.

Head of Safety Systems at OpenAI.

Aoyan Li is publicly listed as an author on ByteDance Seed's Seed1.5-Thinking paper and on public GitHub repositories for Multi-SWE-bench and FullStack Bench.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at Tencent Hunyuan and coauthor of the Hunyuan-T1 report.

Public evidence identifies Chao Xin as a ByteDance Seed paper author, including the Seed1.5-Thinking report and the OpenReview paper PAG on LLM self-correction with multi-turn reinforcement learning.

Public sources list Chengyi Wang as a co-author on ByteDance Seed's Seed1.5-Thinking and DAPO publications, indicating work in large language model reasoning and reinforcement learning.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical report.

Fan Xia is publicly listed as an author on ByteDance Seed's Seed1.5-Thinking and Seed Diffusion publications. ByteDance Seed's official LLM team page places this work in large language model research spanning post-training, inference, memory, learning, and interpretability.

Co-author of the Qwen3 Technical Report.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at ByteDance Seed and coauthor of the Seed-Prover-1.5 technical report.

Publicly listed as a co-author on ByteDance Seed's Seed1.5-Thinking report and the official Seed publication "Model Merging in Pre-training of Large Language Models" (2025).

Researcher at NVIDIA and coauthor of the Nemotron Nano 2 report.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Mingji Han is publicly listed as a coauthor of ByteDance Seed's Seed1.5-Thinking report and the DBLP-indexed NSDI 2025 paper ByteCheckpoint, indicating work spanning reasoning-model reinforcement learning and large foundation model infrastructure.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at ByteDance Seed and coauthor of the Seed-Prover-1.5 technical report.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical report.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Public sources list Xiaoyun Zhi as a coauthor on ByteDance Seed's Seed1.5-Thinking report and on 2025 DBLP-indexed papers about robust, reliable, and large-scale LLM training infrastructure at ByteDance.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical report.

Xing Jin is publicly listed as a coauthor on ByteDance Seed publications including Seed1.5-Thinking and Seed-Prover, indicating work connected to reasoning-focused and theorem-proving research.

Xun Zhou is publicly listed as a coauthor on ByteDance Seed research including Seed1.5-Thinking on reasoning with reinforcement learning, Hyper-Connections on neural network architecture for large language model pre-training, and Expert Race on diffusion transformers with mixture-of-experts routing.

Researcher at ByteDance Seed and coauthor of the Seed-Prover technical report.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Researcher at Tencent Hunyuan and coauthor of the Hunyuan-T1 report.

Public sources list Yifan Yang as a coauthor on ByteDance Seed's Seed1.5-Thinking report and on the 2025 LongReason and MIR-Bench papers, indicating work around long-context reasoning and LLM benchmark design.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Public sources identify Yufei Xu as a ByteDance Seed coauthor on Seed1.5-Thinking and on Recitation over Reasoning (RoR-Bench), both related to large language model reasoning.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Publicly listed as a coauthor on ByteDance Seed publications including Seed1.5-Thinking and Seed Diffusion Preview. No uniquely identifying personal homepage or scholar-style profile was confirmed, so this profile remains conservative and publication-based.

Researcher at ByteDance Seed and coauthor of the Seed-Thinking-v1.5: Advancing Superb Reasoning Models with Reinforcement Learning.

Research scientist in Tongyi Lab whose public profile highlights work on speech processing, machine learning, and multimodal large language models.

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

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

Public report authorship links Hui-Ling Zhen to the Nemotron-4 340B Technical Report at NVIDIA.

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

Public report authorship links Mingxuan Wang to Voxtral at Mistral AI.

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

Zihao Huang is listed as an author of the Moonshot AI technical report Kimi-VL Technical Report.

Xifeng Yan is a professor at UC Santa Barbara whose research focuses on data mining, machine learning, and graph analytics. His public profile highlights work on graph mining, large-scale data systems, and AI methods for structured data.

Amro El-Jaroudi is listed as an author of the Microsoft technical report Phi-4-mini-reasoning: Exploring the Limits of Small Reasoning Language Models in Math.

Andrew Mao is listed as an author of the Microsoft technical report Phi-4-mini-reasoning: Exploring the Limits of Small Reasoning Language Models in Math.

Donghai Wu is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Ellen Zhang is listed as an author of the Microsoft technical report Phi-4-reasoning Technical Report.

Harika Kondragunta is listed as an author of the Microsoft technical report Phi-4-reasoning Technical Report.

Jie Tang is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Julien Besombes is listed as an author of the Mistral AI technical report Magistral: Efficient Training of Small Language Models for Reasoning.

Li Dong is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Marc'Aurelio Ranzato is listed as an author of the Mistral AI technical report Magistral: Efficient Training of Small Language Models for Reasoning.

Matthias Freitag is listed as an author of the Microsoft technical report Phi-4-mini-reasoning: Exploring the Limits of Small Reasoning Language Models in Math.

Penghui Wei is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Qingqing Li is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Saffet Kaya is listed as an author of the Mistral AI technical report Magistral: Efficient Training of Small Language Models for Reasoning.

Yeonwoo Choi is listed as an author of the NVIDIA technical report NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model.

Yili Zeng is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Yukun Zhu is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Yuxiang Zheng is listed as an author of the Qwen technical report QwQ-32B: Embracing the Power of Reinforcement Learning.

Zeyu Zhang is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Zichen Li is listed as an author of the Tencent Hunyuan technical report Hunyuan-T1: Scaling Up Test-Time Compute with Open-Source Reinforcement Learning.

Hongbin Ren is publicly listed as a co-author on ByteDance Seed publications including Seed1.5-Thinking and Model Merging in Pre-training of Large Language Models.

Publicly listed as an author of ByteDance Seed's Seed1.5-Thinking (arXiv, 2025) and as a coauthor of MegaScale: Scaling Large Language Model Training to More Than 10, 000 GPUs (NSDI 2024, via DBLP).

Publicly listed as an author on ByteDance Seed's OSDI 2025 paper "Understanding Stragglers in Large Model Training Using What-if Analysis" and on the Seed1.5-Thinking report author list.

Publicly listed as a coauthor on ByteDance Seed's Seed1.5-Thinking and Seed Diffusion publications, indicating work related to reasoning and diffusion language models.

Research scientist at Mistral AI working on deep learning, language technologies, and large-scale AI systems.

Machine learning researcher at ByteDance AI Lab.

Distinguished Scientist and corporate vice president at Microsoft Research whose public work spans language models, search, and reasoning; arXiv author results include Phi-4 mini reasoning.

Principal Research Manager at Microsoft Research AI4Science leading language AI and foundation model work; his arXiv author results include the Phi-4 reasoning reports.

Principal researcher at the Technology Innovation Institute working on computer vision, multimodal and embodied AI, data-centric AI, and satellite image understanding.

Associate chief researcher at the Technology Innovation Institute working on efficient generative AI and AI models for science.

Researcher working on reasoning-focused language models, including OpenAI o1.

Machine learning researcher and writer focused on mechanistic interpretability, music generation, and image or video diffusion; contributed to OpenAI's o1 system-card work.

Researcher at Microsoft working on machine learning, natural language processing, and information retrieval.

Research scientist at Mistral AI working on language models for code.

Research scientist at Microsoft working on large language models and generative AI.

Research scientist at Microsoft AI working on language models, previously at FAIR and the University of Southern California.

Ziwen Xu is publicly listed as an author on ByteDance Seed's Seed1.5-Thinking report and on the official Seed paper page for Model Merging in Pre-training of Large Language Models.

Mona Jalal

Yuxiang Zheng

Ming-Yu Liu

Xueyan Zou

Arash Vahdat

Dilek Hakkani-Tur

Kartikeya Mangalam

Hang Zhu

Renjie Zheng

Xiangpeng Wei

Yuwen Xiong

Junyang Lin

Shyamal Anadkat

Yong Shan

Ming Lin

Raphael Ho

Junxian He

Jianhui Duan

Xingyan Bin

Zhiqi Lin

Zihan Liu

Guillaume Lample

Guanghan Ning

Qi Liu

Qiyang Min

Chenwei Lou

Abhinav Khattar

Alec Radford

Shiyu Tian

Jiangjie Chen

Qiying Yu

Yongfei Liu

Ziheng Jiang

Haobin Jiang

Qingping Yang

Siyu Yuan

Weinan Dai

Grace Lam

Aleksandra Piktus

Boxin Wang

Zewei Sun

Ning Dai

Yao Luo

Yufeng Yuan

Zhuolin Yang

Ching-Yao Chuang

Zihan Wang

Ning Wu

Qianyu He

Ahmed H. Awadallah

Kaihua Jiang

Rogerio Feris

Kai Hua

Bairen Yi

Yangyi Chen

Jingren Zhou

Alex Ficek

Defa Zhu

Chen Dun

Wenchang Ma

Xunhao Lai

Yiyuan Ma

Lin Yan

Sijun Zhang

Wenlei Shi

Chenggang Li

Jiazhan Feng

Kang Liu

Thomas Scialom

Tianyang Zhan

Ameet Talwalkar

Mujeen Sung

Sandhini Agarwal

Yuhua Jiang

Shengding Hu

Thomas Wolf

Haibin Lin

Chengzhi Wei

Feng He

Lihua Qian