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I am a fifth-year PhD student in the Algorithms, Combinatorics, & Optimization (ACO) program at Georgia Tech, working with Santosh Vempala. I did my undergrad in Electrical & Computer Engineering, also at Georgia Tech.

I am fascinated by the study of intelligence, both biological and artificial. My research on this topic focuses on a few questions:

• What theoretical models of the brain at the level of neurons can we construct?
• Can these models replicate the brain’s greatest trick (its ability to learn, and especially to learn to reason abstractly)?
• What can we prove?
• From this theoretical foundation, can we derive efficient and generalizable machine learning systems?

Outside of research I love music, which is doubtlessly thanks to many years of training in piano performance and composition at the Suzuki Music Institute of Dallas where I studied with Dr. Bret Serrin. I also enjoy cooking, reading (fiction mostly), and the great outdoors.

Finally, I organize the ACO Student Seminar. Contact me if you’re interested in giving a talk!

Teaching

CS6550/8803: Continuous Algorithms - Optimization and Sampling (Teaching Assistant)

CS 4540: Advanced Algorithms (Teaching Assistant)

Papers

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Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies with Dan Mitroposky, Christos Papadimitriou, & Santosh Vempala

Computation with sequences of assemblies in a model of the brain (ALT 2024, Neural Computation [in press])

with Christos Papadimitriou & Santosh Vempala

Aligning latent representations of neural activity (Nature BME)

with Konrad Kording & Eva Dyer

Seeing the forest and the tree: Building representations of both individual and collective dynamics with transformers (NeurIPS 2022)

with Ran Liu, Mehdi Azabou, Jingyun Xiao, & Eva Dyer

Assemblies of neurons learn to classify well-separated distributions (COLT 2022) (Presentation recording)

with Christos Papadimitriou & Santosh Vempala

Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activity (NeurIPS 2021)

with Ran Liu, Mehdi Azabou, Chi-Heng Lin, Mohammad Gheshlaghi Azar, Keith Hengen, Michal Valko, & Eva Dyer

Mine your own view: Self-supervised learning through across-sample prediction (NeurIPS Workshop on Self-Supervised Learning 2021)

with Mehdi Azabou, Ran Liu, Keith Hengen, Eva Dyer, et al.

Learning with plasticity rules: Generalization and robustness

with Rares Cristian, Christos Papadimitriou, & Santosh Vempala

Barycenters in the brain: An optimal transport approach to modeling connectivity (NeurIPS Workshop on Optimal Transport 2019)

with Eva Dyer

Hierarchical optimal transport for multi-modal distribution alignment (NeurIPS 2019)

with John Lee, Eva Dyer, & Chris Rozell

Contact Me

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[first][last]@gatech[dot]edu