Serena L. Wang


I am a final-year PhD student in Computer Science at University of California, Berkeley, advised by Michael I. Jordan. I am generously supported by the NSF Graduate Research Fellowship and the Apple Scholars in AI/ML PhD fellowship. I have also concurrently worked at Google Research at 20% time for the last six years, where I am part of the Discrete Algorithms Group with Ravi Kumar and have also worked with Maya Gupta on the Glassbox Machine Learning Research team.

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, the political economic analysis of multi-agent incentives, and better qualitative understanding of problem formulation. I employ tools from robust optimization, statistics, learning theory, and economics.

Email: serenalwang (at)