I am a postdoctoral fellow at Harvard’s Center for Research on Computation and Society (CRCS), hosted by Ariel Procaccia. In 2026, I will be joining the University of British Columbia as an assistant professor of Computer Science.
I have also concurrently worked with Google Research at 20% time for the last seven years, where I have had the privilege of working with amazing mentors including Ravi Kumar, Preston McAfee, and Maya Gupta. I received my PhD in Electrical Engineering and Computer Science at the University of California, Berkeley, advised by Michael I. Jordan. My PhD research was supported by the Apple Scholars in AI/ML PhD Fellowship and the NSF Graduate Research Fellowship.
My research focuses on understanding and improving the long term societal impacts of machine learning by rethinking ML algorithms and their surrounding incentives and practices. I’m particularly interested in gaps between metrics and goals, and how those gaps may be bridged through algorithmic improvements, analysis of multi-agent incentives and interdependence, and better understanding of intervention context. I employ tools from machine learning, economics, statistics, and optimization.
Email: serenalwang (at) g.harvard.edu