Autonomous LLM Agents: Risks and Scientific Challenges

Yu Su is a Distinguished Assistant Professor of Computer Science and Engineering at The Ohio State University, where he co-directs the NLP group. He has broad interests in artificial intelligence, with a primary interest in the role of language as a vehicle for reasoning and communication. His recent work covers many facets of AI agents including memory, planning, grounding, and safety. He is a 2025 Sloan Research Fellow and has received multiple paper awards from CVPR and ACL.

Alane Suhr is an Assistant Professor of Computer Science at UC Berkeley, affiliated with the Berkeley AI Research (BAIR) Lab. Alane’s research focuses on language use and learning in interaction, especially situated and collaborative interactions; agents that use language and language-conditioned agentic systems; and language grounding to perception and action.

Victor Zhong is an Assistant Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, and a Canada CIFAR AI Chair at the Vector Institute. His research is on efficient machine learning methods that interpret language to generalize to new problems. His group, the Reading to Learn Lab, works on grounded language agents, test-time adaptation, and learning from language feedback. Victor received a PhD in Computer Science from the University of Washington, a Master’s in Computer Science from Stanford University, and a Bachelor’s in Computer Engineering from the University of Toronto.

Yoshua Bengio is a full professor in the Department of Computer Science and Operations Research at Université de Montréal, as well as the Special Advisor and Founding Scientific Director of IVADO and Scientific Advisor and Founder of Mila . He holds a Canada CIFAR AI chair and is the recipient of the 2018 A.M. Turing Award, considered the “Nobel Prize of computing.”

He is a fellow of both the U.K.’s Royal Society and the Royal Society of Canada, an officer of the Order of Canada, a knight of the Legion of Honor of France, and a member of the U.N.’s Scientific Advisory Board for Independent Advice on Breakthroughs in Science and Technology.

Dawn Song is a Professor in Computer Science at UC Berkeley and Co-Director of Berkeley Center for Responsible Decentralized Intelligence. Her research interest lies in AI and deep learning, security and privacy, and decentralization technology. She is the recipient of various awards including the MacArthur Fellowship, the Guggenheim Fellowship, the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review TR-35 Award, ACM SIGSAC Outstanding Innovation Award, and more than 10 Test-of-Time Awards and Best Paper Awards from top conferences in Computer Security and Deep Learning. She has been recognized as Most Influential Scholar (AMiner Award), for being the most cited scholar in computer security. She is an ACM Fellow and an IEEE Fellow. She obtained her Ph.D. degree from UC Berkeley. She is also a serial entrepreneur and has been named on the Female Founder 100 List by Inc. and Wired25 List of Innovators.

Chris Pal is a world renowned expert in deep learning (DL), probabilistic machine learning and applied AI. He received a Google focused faculty Research Award twice (in 2017 and in 2009). He brings a unique multidisciplinary expertise to the team with his strong theoretical background (DL, graphical models, causality, etc.) as well as his key expertise in Natural Language Processing and Computer Vision applied to a wide range of applications domain (medical imaging in health care, satellite imaging for biodiversity and climate change, autonomous driving related to transportation).