I am a fifth-year Ph.D. candidate in Electrical Engineering and Computer Sciences at UC Berkeley, advised by Jennifer Listgarten and Michael I. Jordan. I am a member of BAIR and work on statistical learning and inference methods for engineering biological systems. Prior to Berkeley, I was a Google AI Resident and also conducted marine biologging fieldwork with Kakani Katija at the Monterey Bay Aquarium Research Insitute. I received my B.S. in Computer Science in 2016 from Stanford University, where I was fortunate to work with Marius Cătălin Iordan, Fei-Fei Li, and Stephen Boyd. My work is generously supported by an NSF Graduate Research Fellowship.
Beyond research, I am an avid hiker, religious fan of artistic gymnastics, and proud mom to an extraordinary son.
I can be reached at clarafy at berkeley dot edu.
select recent work
Clara Fannjiang, Stephen Bates, Anastasios N. Angelopoulos, Jennifer Listgarten, and Michael I. Jordan. 2022. Conformal prediction for the design problem. Proceedings of the National Academy of Sciences, to appear. arXiv code
Clara Fannjiang, T. Aran Mooney, Seth Cones, David Mann, K. Alex Shorter, and Kakani Katija. 2019. Augmenting biologging with supervised machine learning to study in situ behavior of the medusa Chrysaora fuscescens. Journal of Experimental Biology, 222, jeb207654. PDF publication jellyfish footage code
recent and upcoming invited talks
Conformal prediction for the design problem. Machine Learning for Protein Engineering Seminar, October 18, 2022.
Conformal prediction for the design problem. AIDD Summer School on Advanced Machine Learning for Drug Discovery, May 13, 2022. program
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"A man can't be always defending the truth; there must be a time to feed on it."
C. S. Lewis, Reflections on the Psalms (1958)