I am a PhD candidate in Electrical & Computer Engineering at Georgia Tech, largely interested in characterizing learning and intelligence in artificial and biological systems. Towards these ends, I spend my time studying both machine learning and theoretical + computational neuroscience, with a healthy smattering of many topics in applied mathematics.
Much of my proposed work revolves around and studies different aspects of representation learning with an eye towards explaining complex, hierarchical information processing systems. In particular I look to leverage the geometric structure of representations found in both artificial & biological neural networks so as to render them more interpretable, and thereby discover their governing principles. Some ideas that I actively think about in these contexts are:
My long-term goal is to use math & engineering to develop computational methods that effectively characterize changes in structure, organization, and information processing in the brain across different stages of neurological age, health, and development. I subsequently hope to employ these insights in the development of better ML/AI systems that require less supervision and/or data, learn progressively, and are more amenable to changes in task structure.
Machine Learning: Unsupervised/self-supervised learning, dimensionality reduction & manifold learning, generative models, metric/similarity learning, and learning with structured sparsity.
Mathematics: Matrix & tensor decompositions, column subset selection, low-rank approximation, metric embeddings, convex geometry, optimization, group & representation theory, differential geometry & topology, and information geometry.
Neuroscience: Neural coding & decoding, representational learning, models of brain structure & organization, and connectomics.
Outside of academic and scientific pursuits, my hobbies include reading, listening to (rather old) music, watching + playing racket sports, and solving the classic 3x3 Rubik’s cube along with its many variants. I am incredibly fond of cats, enjoy history of almost any kind, have been a Federer fan for far too long, and remain a Bombay kid at heart for life.