Welcome to my site :)

I’m a Bioinformatics PhD student at UCLA interested in computational neuroscience and representation learning. In particular, I want to understand a) how the retina generates signals that are robust to varying conditions, and b) how we can use these properties in neural networks to make models robust to noise. My recent work has focused on regularizers that separate signal and nuisance variation so that models perform well on out of distribution corruptions. I’m now focused on understanding various retinal ganglion cell type functionality and what they add to visual representations.

I’m lucky to be advised by Dr. Joel Zylberberg at UCLA. Prior to starting my PhD, I was fortunate to be mentored by Dr. Patrick Ellinor at the Broad Institute, Dr. Radhika Atit at Case Western Reserve University, and Dr. Stefan Heller at Stanford.

In my free time, I enjoy photography, backpacking, weightlifting, and cooking.

Updates

• Sep 2026New preprint on signal-noise factorization regularization for neural networks was posted on arXiv.
• Sep 2025Started my PhD in Bioinformatics at UCLA.
• Jul 2025Wrapped up two years as a Computational Associate in Patrick Ellinor’s group at the Broad Institute.
• Nov 2024Presented a poster on Contrack, a contractility screening platform for 3D cardiac microtissues, at AHA Scientific Sessions in Chicago.
• Mar 2024Review on fibrosis-associated depletion of lipid-filled cells published in Experimental Dermatology.