I am a final year EECS PhD student in the Theory Group at Berkeley, where I am lucky to be advised by Satish Rao. I was previously funded by an NSF GRFP Fellowship.

I Fall 2022, I was an Applied Scientist Intern at AWS, and had a great time working with James Cook and Nina Mishra. In Summer 2021 and Summer 2022, I had a fantastic experience with the Mathematics of AI group at IBM, working with Ken Clarkson and Shashanka Ubaru. Before grad school, I was an engineer at Two Sigma Investments. I received my BA in Mathematics from Princeton in June 2016, where I had the good fortune to be advised by Maria Chudnovsky.

My research interests include spectral graph theory, high-dimensional geometry, and sampling/MCMC. Through my internships, I also have experience with neural network compression, sketching algorithms, and differential privacy.

Inclusion of Forbidden Minors in Random Representable Matroids[arXiv] Jason Altschuler, Elizabeth Yang.* Discrete Mathematics, 2017.

Competition Graphs Induced by Permutations[arXiv] Brian Nakamura, Elizabeth Yang* Preprint, 2015. Presented at the 2015 Joint Mathematics Meetings.

*Authors are listed in alphabetical order; this is convention for theoretical computer science and math.

Teaching

At Berkeley, I was the instructor of CS 70 (Discrete Math and Probability) during Summer 2019. I was also a GSI for CS 70 Fall 2018, and received an Outstanding GSI award.

At Princeton, I was a TA for Introductory Number Theory (MAT 214), Introductory Real Analysis (MAT 215), Group Theory (MAT 345), and Graph Theory (MAT 375).

Outreach & Mentorship

I am very passionate about STEM outreach, especially getting younger students excited about math. Moving forward, I seek opportunities to promote diversity in these fields.