I am a third-year computer science PhD student at Cornell, where I am fortunate to be advised by Nikhil Garg and Jon Kleinberg. Previously, I completed my undergraduate degree in mathematics at Princeton, where I was lucky to work closely with Arvind Narayanan and Evita Nestoridi.
I am based at Cornell Tech in New York City, where I am a member of Cornell's AI, Policy, and Practice (AIPP) working group. In Summer 2024, I was a PiTech fellow, working on the Restorative Record.
I'm interested in using AI to understand and improve societal systems (like social media, hiring, and school matching). I'm also interested theoretical aspects of matching markets and recommender systems.
Sparse Autoencoders for Hypothesis Generation
Preprint. Try the demo. To use, pip install hypothesaes.
arXiv:2411.09716
Monoculture in Matching Markets
NeurIPS 2024
Reconciling the Accuracy-Diversity Trade-off in Recommendations
WWW 2024, Oral Presentation
REFORMS: Reporting Standards for Machine Learning Based Science
Science Advances (2024)
The Largest Vocabulary Without a Crossword
Working paper
Mitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers
NeurIPS 2021, Track on Datasets and Benchmarks, Oral Presentation
Covered in MIT Technology Review, Nature, VentureBeat. Summarized in this Twitter thread.
Mixing Times of One-Sided k-Transposition Shuffles
Under revision at Annals of Applied Probability
Deep Residual Networks Preserve Expected Length
Undergraduate thesis advised by Boris Hanin
Sigma Xi Book Award for outstanding undergraduate research in mathematics