About Me
I am a Junior Fellow of the Harvard Society of Fellows. My research interests lie in some neighborhood of the intersection between theoretical neuroscience, statistical physics, and machine learning. For more information about my work, see some of my recent publications, as well as my teaching experience and expository notes.
I earned my doctorate in physics at Harvard, under the supervision of Cengiz Pehlevan. My thesis considered a few topics in the statistical mechanics of neural networks. Before that, I did my undergraduate work in physics at Yale, where I worked with Damon Clark on visual motion detection and locomotor coordination in fruit flies.
News from the past year
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[4 April 2024] I’ve defended my thesis! It is available here.
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[March 2024] Three posters on our work were presented at Cosyne 2024! I also had the pleasure of speaking at the “Comparative approaches to advance neural circuits and computation” workshop organized by Anqi Zhang and Siddharth Jayakumar.
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[December 2023] I’m presenting three papers at NeurIPS 2023! Check out our work with Paul Masset on models for fast inference in the olfactory bulb, our work with Hamza Chaudhry and Dima Krotov on associative memory for long sequences, and our work on learning curves for models with many layers of structured features. Also check out Hamza’s talk at the AMHN workshop.
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[September 2023] I had the pleasure of presenting our work on the geometry of distributed neural codes for fast inference and in deep networks at the Washington University in St. Louis Computational Neuroscience Next Generation (CNNG) Symposium.
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[August 2023] I spoke about our work on deep linear Bayesian neural networks at the Statistical Physics and Machine Learning Back Together Again workshop in Cargèse. Slides from my talk have been posted on the workshop website.