Serena L. Wang


I am a final-year PhD student in Computer Science at University of California, Berkeley, advised by Michael I. Jordan. I have also concurrently worked with Google Research at 20% time for the last six years, where I have had the privilege of being mentored by amazing folks including Ravi Kumar, Preston McAfee, and Maya Gupta. I am 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, robust optimization, causal inference, and most recently, economics.

Email: serenalwang (at)