I'm a PhD student in theoretical physics at Harvard. I am interested in using a variety of approaches to gain insight into computation and generalization in neural systems. 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 nonlinear, strongly-interacting systems at their phase transitions. I also had the opportunity to learn from Philsang Yoo about the connections between quantum field theory and the Langlands program.

I am excited by the intersection of machine learning and computational neuroscience. I first worked under John Murray as an undergrad, modeling the dynamics of working memory in recurrent neural networks (RNNs) and for Google, developing convolutional neural network (CNN) models for computer vision and face recognition for the internet of things.

My past collaborations with Dr. Erik Schnetter at the Perimeter Institute for Theoretical Physics, focused on finding ways around the curse of dimensionality in Einstein's field equations. You can learn more about this work from our arXiv paper and implementation on Github.

*This website serves as a repository for my research and personal projects. If you are interested in any of these projects, feel free to reach out.
*

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

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

**(2021) In Submission **
[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 2019)** [Final Presentation]

**(Summer 2016)** [Lecture]

**(Fall 2013)** [PDF]

**(Fall 2013)** [PDF]