Faculty Friday with Chris Amato: Training Intelligent Machines Through Real-World Interactions

Christopher Amato


In this week’s Faculty Friday video, Northeastern University Assistant Professor and EAI faculty member Chris Amato describes how reinforcement learning enables intelligent interactions between humans and machines.



As an assistant professor at Northeastern University, Christopher Amato leads the Lab for Learning and Planning in Robotics. Before joining Northeastern, Dr. Amato was a research scientist at Aptima, Inc., a Postdoc and Research Scientist at MIT, and an Assistant Professor at the University of New Hampshire.

Dr. Amato has had several papers published at leading artificial intelligence, machine learning, and robotics conferences. He won the Best Paper Prize at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) in 2014. Dr. Amato received a nomination for Best Paper at the Robotics: Science and Systems conference in 2015, the Associate for the Advancement of Artificial Intelligence conference in 2019, and AAMAS in 2021. He has also won several awards, such as Amazon Research Awards and an NSF CAREER Award. 

Dr. Amato’s research focuses on reinforcement learning and planning in partially observable and multi-agent/multi-robot systems.