I'm a PhD candidate in theoretical physics at Harvard. I am interested in using approaches from statistics and physics to gain insight into the structure and dynamics of learning algorithms, particularly neural networks. I am advised by Cengiz Pehlevan. My work is funded by the US Department of Defense through the NDSEG Fellowship and by the Fannie and John Hertz Foundation.

I received my B.S. in physics and M.S. in mathematics from Yale in 2018. There, I performed research under David Poland, studying conformal field theory in dimensions three and four using the bootstrap program. Conformal field theory is a powerful idea that allows us to gain insight into strongly-interacting systems at their phase transitions. Concurrently, I had the opportunity to learn from Philsang Yoo about the connections between quantum field theory and the Langlands program.

In the past, I have interned at Google, where I developed convolutional neural network models in computer vision for the internet of things. I also performed research under John Murray, modeling the dynamics of working memory in recurrent neural networks. Also throughout my undergrad, I worked at the Perimeter Institute for Theoretical Physics, collaborating with Dr. Erik Schnetter on finding ways around the curse of dimensionality in numerically solving partial differential equations.

**(2021) ICLR 2022 **
[arXiv]

**(2021) In Submission **
[arXiv]

**(2021) eNeuro **
[Journal Link]
[bioRxiv] [Code Repository]

**(2021) Physical Review D **
[Journal Link]
[arXiv] [IAS Talk]

**(2021) Journal of High Energy Physics **
[Journal Link]
[arXiv]
[Princeton Talk]

**(2018) Journal of High Energy Physics**
[Journal Link]
[arXiv]
[Code Repository]

**(2018) Yale Senior Thesis** [PDF] [Presentation Slides]

**(2017) ** [arXiv] [PDF]
[Code Repository]

**(2017) Physical Review A** [Journal Link] [PDF]

**(Fall 2015)** [PDF]

**(2019-2020)** [PDF]

**(Spring 2020)** [PDF]

**(Fall 2018)** [PDF]

**(Fall 2018)** [PDF]
[Chapter 1: Black Holes and the Holographic Principle]
[Chapter 2: Matrices and Strings]
[Chapter 3: Holographic Duality]

**(Spring 2018)** [Lecture 1] [Lecture 2]

**(Fall 2017)** [PDF]

**(Spring, Fall 2017)** [Full Notes] [Part 1: Categorical Harmonic Analysis]
[Part 2: Moduli Space of Bundles]
[Part 3: Geometric Satake]
[Part 4: Geometric Representation Theory]
[Part 5: Intro to Derived Algebraic Geometry]
[Part 6: Back to Basics]
[Part 7: Singular Support]
[Part 8: Revisiting D(Bun_G)]
[Part 9: How to study D(Bun_G)]
[Part 10: Factorization Structures]
[Part 11: Fundamental Local Equivalence]

**(Spring, Fall 2017)** [Spring Talk] [Fall Talk]

**(Fall 2016)** [PDF]

**(Fall 2016)** [Review notes on Fiber Bundles]
[Talk 1] [Talk 2]

**(Spring 2016)** [PDF]

**(Spring 2016)** [PDF]

**(Summer 2020)** [Final Paper]

**(Summer 2019)** [Final Presentation]

**(Summer 2016)** [Lecture]

**(Fall 2013)** [PDF]

**(Fall 2013)** [PDF]