Hi!

I’m a PhD student at Berkeley and NSF GRFP fellow, working at the intersection of ML and scientific design (proteins, materials). I’m advised by Jennifer Listgarten and Sergey Levine. Lately I’ve been interested in understanding how domain-specific aspects of the scientific design problems I work on interact with various models and design algorithms. For instance, how might we enable experimentalists to more precisely specify the details of their problem settings and design desiderata?

During my undergrad (Caltech), I primarily spent time thinking about adaptive experiment design, Bayesian inference, GPs, and uncertainty quantification in Yisong Yue’s group. I also had a lot of fun teaching a variety of the core CS / ML courses.

Selected Publications

Leveraging Discrete Function Decomposability for Scientific Design [DADO blogpost]
JC Bowden, S Levine, J Listgarten
International Conference on Learning Representations (ICLR) 2026

Active learning-assisted directed evolution
J Yang, RG Lal, JC Bowden, R Astudillo, MA Hameedi, S Kaur, M Hill, Y Yue, FH Arnold
Nature Communications 2025

For a complete list, see my Google Scholar page.

Outside of work, some things I sometimes like

If anything (or nothing) resonates with you, poke me and let’s get coffee or hang out somewhere in the real world. I’m quite interested in people, broadly, and enjoy making a new friend :p

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