I'm a postdoc in the Department of Physics at University of California San Diego. Currently, my work focuses on applying information theory and statistical mechanics to generative AI algorithms, in particular, diffusion models.
I am broadly interested in importing ideas from physics to machine learning. I love cross-pollinating ideas from different disciplines. This approach stems from my core belief that the universe does not self-factorize into distinct academic disciplines. Nature is economical in its creativity; the same structural motifs often reappear in problems that, at first glance, seem unrelated.
I did my PhD in Theoretical Physics from the University of California San Diego under the nurturing guidance of Daniel Green. After that, I spent three eventful years at the University of Chicago under Austin Joyce. It was at Chicago that I became interested in diffusion models. I also benefitted from the mentorship of Lorenzo Orecchia at this time.
