BAAI CONFERENCE

Dr.Wang Jian is a distinguished expert in cloud computing technology, Founder of Alibaba Cloud, Director of Zhejiang Lab, and Member of the Chinese Academy of Engineering. He pioneered the data-centric distributed cloud computing architecture and took the lead in proposing the industrial model of computing as a public service. He spearheaded the R&D of the Alibaba Cloud platform with independent intellectual property rights, which is built around Feitian, a large-scale distributed computing system. His work has greatly strengthened China’s discourse power in the global cloud computing sector and enabled the country’s cloud computing industry to embark on development at broadly the same starting level as international peers. In recognition of his outstanding contributions to cloud computing, he was elected a Member of the Chinese Academy of Engineering in 2019.

Huang Tiejun is the chairman of Beijing Academy of Artificial Intelligence, a professor with the School of Computer Science of Peking University, and the director of the National Key Laboratory of Multimedia Information Processing. His main research interests are in visual information processing and brain-like intelligence. He invented the principle of Spiking Continuous Photography and ultra-high-speed visual sensor chips, camera, and system. He was awarded the Second Prize of the National Technology Invention Award in 2017 for efficient visual feature analysis and compression key technologies, the Second Prize of the National Science and Technology Progress Award in 2012 for the development and industrial application of national video coding standards, the Outstanding Contribution Award for Chinese Standard Innovation in 2022, and the Outstanding Contribution Award for the Wu Wenjun Artificial Intelligence Science and Technology Award in 2022.He is also the vice chair of the Steering Committee for the "New Generation Artificial Intelligence Major Project" and the vice chair of the National Artificial Intelligence Standardization Steering Group (National Standardization Committee). He is a National Distinguished Young Scholar, Changjiang Scholar, and Fellow of the CAAI (Chinese Association for Artificial Intelligence), CCF (China Computer Federation), CSIG (China Society of Image and Graphics) and CIE (Chinese Institute of Electronics).

Dr. An Bo is a President’s Chair Professor and the Head of the Department of Artificial Intelligence at Nanyang Technological University (NTU), Singapore. He also serves as the Director of the Nanyang Center for Applied AI. He received his Ph.D. in Computer Science from the University of Massachusetts Amherst in 2011. His primary research interests include artificial intelligence, multi-agent systems, algorithmic game theory, reinforcement learning, and optimization. He has published over 200 papers in top-tier AI conferences and journals, including AAMAS, IJCAI, AAAI, ICLR, NeurIPS, ICML, AISTATS, ICAPS, KDD, UAI, EC, WWW, JAAMAS, and AIJ. Dr. An is an AAAI Fellow, an ACM Distinguished Scientist, and a member of the Board of Directors for both IJCAI and AAAI. He will serve as the Program Chair for IJCAI’27. Currently, he is the Editor-in-Chief of IEEE Intelligent Systems. Selected Honors & Awards: - IFAAMAS Victor Lesser Distinguished Dissertation Award (2010) - INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice (2012) - IEEE Intelligent Systems' "AI's 10 to Watch" (2018) - Nanyang Research Award (2022) - Winner of the Microsoft Collaborative AI Challenge (2017)

Dr. Tang Jie is a Tenured Professor and Deputy Head of the Department of Computer Science and Technology at Tsinghua University. He also serves as the Director of the Tsinghua-CAE Joint Laboratory of Knowledge Intelligence and is a recipient of the National Science Fund for Distinguished Young Scholars. His primary research interests include social network analysis, data mining, machine learning, and knowledge graphs. He has published over 200 papers and holds more than 20 patents. Dr. Tang has served as the Editor-in-Chief of ACM TKDD and as the Program Committee Chair for CIKM’16 and WSDM’15, Associate General Chair for KDD’18, and on the editorial boards of IEEE TKDE, ACM TIST, and IEEE TBD. He is the recipient of numerous prestigious awards, including the Royal Society-Newton Advanced Fellowship, the CCF Young Scientist Award, and the First Prize of the CAAI Science and Technology Progress Award. In 2018, he was honored with the KDD Service Award.

Dr. Wang Zhongyuan, President of Beijing Academy of Artificial Intelligence (BAAI). He was honored in MIT Technology Review's "Innovators Under 35" (TR35) in 2018. He has held pivotal positions at renowned companies such as Kuaishou, Meituan, Facebook, and Microsoft Research Asia, focusing on the development of core artificial intelligence technologies. Dr. Wang has published over 100 academic articles in top-tier international conferences and journals, including winning the Best Paper Award at ICDE 2015. He has authored 3 academic monographs and holds 5 U.S. patents and over 50 Chinese patents. With extensive experience in both AI research and practical product systems such as search & recommendation, his primary research scope includes large-scale models, multimodal AI, search & recommendation systems, embodied artificial intelligence, and VR/AR technologies.

Yu Yang, Professor at the School of Artificial Intelligence, Nanjing University, mainly engages in research on artificial intelligence, machine learning and reinforcement learning. He has obtained five international paper awards and three championships in international algorithm competitions. He was selected into the National Young Talents Program and included in IEEE Intelligent Systems "AI’s 10 to Watch", and received the CCF-IEEE Young Scientist Award and the inaugural Asia Pacific Data Mining Young Achievement Award. He was also invited to deliver a Young Spotlight Talk at IJCAI 2018.

Yu Chao is currently an Assistant Professor at the Shenzhen International Graduate School, Tsinghua University, and has been selected into the Young Talent Support Program of the Chinese Institute of Electronics. Her research has long focused on decision intelligence based on reinforcement learning. She has published over 50 papers as the first or corresponding author in top international conferences and journals such as ICML, NeurIPS, ICLR, CVPR, ECCV, CoRL, IROS, ICRA, TMLR and RAL, with more than 5,500 citations on Google Scholar. Her representative achievements include MAPPO, a multi-agent reinforcement learning algorithm with over 2,800 Google Scholar citations, and RLinf, a large-scale reinforcement learning training framework for embodied intelligence with over 2,600 GitHub stars.

Liu Bang is currently Tenured Associate Professor of the Department of Computer Science at Université de Montréal and Canada CIFAR AI Chair, as well as a member of Mila Quebec AI Institute and Institut Courtois of Université de Montréal. His research focuses on natural language processing and multimodal intelligent integration, covering large models and intelligent agents, multimodal and embodied learning, and AI for Science. He devotes himself to basic research, interdisciplinary applications and open-source ecosystem construction of large models and agents, and his research achievements have been widely applied in industry. He has published more than 100 papers and tutorials in top international journals and conferences in the fields of natural language processing and artificial intelligence as a core author, served as Area Chair of top conferences including NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL and IJCAI, and acted as Action Editor of Neural Networks. He has received numerous honors such as the Amazon Research Award (2025), WAIC Cloud Sail Award (2024 Rising Star, 2025 Bright Star), Université de Montréal Excellence in Research Award, WWW 2023 Best Paper Nomination and George Walker PhD Thesis Award.

Zhu Yutao, Ph.D. from Université de Montréal, is currently a Postdoctoral Fellow at the Gaoling School of Artificial Intelligence, Renmin University of China, and a recipient of Microsoft Star Scholar Program. His research focuses on information retrieval and large language models. He has published numerous papers in top-tier international journals and conferences in artificial intelligence and information retrieval, with over 6,300 Google Scholar citations. He serves as a program committee member for academic conferences including ACL, NeurIPS, ICML, ICLR and SIGIR, and acts as a reviewer for journals such as PNAS and TOIS. He leads the development of the retrieval-augmented generation toolkit FlashRAG, which has garnered more than 3,400 GitHub stars, and boasts extensive research and development experience in the field of search agents.

Zhuge Mingchen serves as a founding member of Recursive. He holds a PhD in Computer Science from KAUST, tutored by Professor Jürgen Schmidhuber, acclaimed as the Father of Modern Artificial Intelligence and the Father of LSTM. His research centers on Coding Agents, Recursive Self-Improvement (RSI) and Neural Computers. He launched in-depth studies on RSI starting from 2023, putting forward landmark works such as MetaGPT, GPTSwarm, Agent-as-a-Judge and Neural Computer. MetaGPT stands as one of the earliest LLM-based coding agents; GPTSwarm represents an initial RSI system paradigm for large language models; Agent-as-a-Judge pioneers continuous feedback and self-assessment mechanisms for long-duration tasks; Neural Computer establishes an internalized runtime framework combining memory, reasoning and autonomous evolution. He has published over 20 high-level papers with total citations exceeding 6,000, seventy percent of which are first-author publications. His open-source projects have gained more than 130,000 GitHub Stars. Six of his papers have been selected for oral presentations at top conferences in recent three years. He has won the Best Paper Award of NeurIPS Ro-FoMo Workshop, received Outstanding Paper Nomination at EMNLP 2025, and was named Outstanding Reviewer of CVPR 2023. Currently, he initiates and leads the ICLR 2026 RSI Workshop, and acts as Area Chair of COLM 2026 and ACM CAIS 2026.

XinLong Wang , whose primary research focuses on multimodal world models, received his bachelor's degree from Tongji University and his Ph.D. from the University of Adelaide.

Chongxuan Li is an Associate Professor and Doctoral Supervisor at the Gaoling School of Artificial Intelligence, Renmin University of China. His research focuses on the foundational theories, modeling paradigms, large-scale training strategies, and efficient sampling algorithms of generative models. He led the team to develop the large diffusion language model LLaDA, with the model series surpassing 6 million downloads. Multiple of his research outcomes have been deployed in industry-leading large models such as DALL·E 2, Vidu, and Seedream 4.0, attracting over 13,000 Google Scholar citations. He was awarded the Outstanding Paper Award at ICLR 2022 (a top-tier international conference in machine learning) and the First Prize of the Wu Wenjun AI Natural Science Award. He has spearheaded the National Natural Science Foundation of China (NSFC) Young Scientists Fund (Category B), and has been selected as a BAAI Scholar, a recipient of the Wu Wenjun Exceptional Youth Award, and a Beijing Nova. He serves as an Associate Editor for IEEE TPAMI and an Area Chair for international conferences including ICLR, ICML, and NeurIPS. Additionally, he served as the editor-in-chief for the published textbook Ten Lectures on Large Models, and his advised doctoral students have been selected for the NSFC Undergraduate/Graduate Research Program and the ByteDance Scholars Program.