I’m a research scientist working on theoretical neuroscience & deep learning 

I'm interested in building interpretable AI systems and uncovering principles of neural representation in brains and machines. Some topics I've worked on include: geometric/topological deep learning, deep generative models, mechanistic interpretability, symmetry discovery, and neural population decoding.

I received my PhD from UC Berkeley in 2021, under the mentorship of Bruno Olshausen in the Redwood Center for Theoretical Neuroscience. I’m currently appointed as a Postdoctoral Scholar in the Department of Electrical and Computer Engineering at UC Santa Barbara, where I work with Nina Miolane in the Geometric Intelligence Lab. I have an interdisciplinary background that includes applied mathematics, linguistics, cognitive science, and philosophy, in addition to machine learning and neuroscience.

My research has been supported by the PIMS-Simons Postdoctoral Fellowship, the NSF GRFP, and the Beinecke Scholarship. I’ve worked as a researcher in Intel’s Neuromorphic Computing Lab and AI Division. I co-organize the NeurIPS Workshop on Symmetry and Geometry in Neural Representations and the ICML Workshop on Topology, Algebra, and Geometry in Machine Learning

I’m based in San Francisco, with frequent trips to SoCal and Europe. Outside of research, I produce electronic music, DJ, and am a founding member of algorithmic art collective AV Club SF. Reach out if you’re interested in collaborations, community organization, or chatting about the intersection of deep learning, neuroscience, mathematics, art, and technology.