Serena Booth studies how people write specifications for AI systems and how people assess whether AI systems are successful in learning from their specifications. Serena's work is often conducted in the context of reinforcement learning, and her work is sometimes physically embodied, too, i.e. as robots.
Prior to joining Brown University, Serena Booth served as an AI Policy Advisor through a AAAS Fellowship in the U.S. Senate. She worked for the Committee on Banking, Housing, and Urban Affairs to legislate, regulate, and govern AI systems in these high-stakes and high-risk areas. Serena has launched a CNTR AI Policy Summer School at Brown that brings top computing graduate students from across the nation to learn about practical policymaking in AI and technology. As an AI and policy researcher, Serena is passionate about studying how AI will affect workers and consumers, and intervening in the development of the technology to ensure socially-beneficial outcomes for these critical stakeholders.
Serena received her PhD at MIT CSAIL in 2023. She is a graduate of Harvard College (2016) and former Associate Product Manager at Google. Her research has been supported by the National Science Foundation, the Canadian Institute for Advanced Research, the Survival and Flourishing Fund, and the UK AI Security Institute. She has been recognized as a CIFAR Global Scholar (2025), Human-Robot Interaction Pioneer (2023), and as a Rising Star in Electrical Engineering and Computer Science (2022).
