Brian Williams
Professor, Department of Aeronautics and Astronautics
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Brian C. Williams is a professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro) and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), where he leads the Model-based Embedded and Robotic Systems group. He is a pioneer in the fields of risk-aware autonomous systems, qualitative reasoning, and model-based diagnosis, and co-led the development of the NASA Remote Agent system, demonstrated on Deep Space One. His research focuses on creating long-lived systems that seek information autonomously and act safely, while commanding, diagnosing and repairing themselves using fast, commonsense reasoning and machine learning. His interests include neural symbolic systems, active learning in risky environments, reasoning at reactive time scales, cooperative and space robotics, intelligent embedded systems, model-based reactive planning, execution and diagnosis, data-driven exploratory modeling, semantic interpretation and hybrid system control. Before coming to MIT, he worked at the Xerox Palo Alto Research Center and NASA Ames Research Center. He earned an SB and a PhD in electrical engineering and computer science from MIT.
Selected Publications
- Olkin, J., Parimi, V., & Williams, B. C. (2024). Multi-agent Vulcan: An information-driven multi-agent path finding approach. In Proceedings of the 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 10253–10259). IEEE.
- Parimi, V., Hong, S., & Williams, B. (2024). Task-driven risk-bounded hierarchical reinforcement learning based on iterative refinement. Proceedings of the AAAI Symposium Series, 3(1), 573–575.
- Zhang, Y., Robertson, P., Shu, T., Hong, S., & Williams, B. C. (2024). Risk-bounded online team interventions via theory of mind. In Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA) (pp. 12964–12970). IEEE.
Media
- May 19, 2022: Charting a safe course through a highly uncertain environment
- April 21, 2022: Anticipating others’ behavior on the road
- April 23, 2020: MIT News, Reporting tool aims to balance hospitals’ Covid-19 load.