I am a graduate student in the Computer Science
department at the University of Pennsylvania, where I am fortunate to be advised by Michael
Kearns and Aaron Roth. Previously, I was an undergrad at Georgia Tech where I studied Computer Science and Public Policy.
My research interests are in machine learning and game theory, with applications in algorithmic fairness, privacy, and robustness.
I enjoy talking with students about research so please get in touch if you want to discuss my work!
Multicalibrated Regression for Downstream Fairness. Joint with Ira Globus-Harris, Chris Jung, Michael Kearns, Jamie Morgenstern, Aaron Roth. Preprint.
Practical Adversarial Multivalid Conformal Prediction. Joint with Osbert Bastani, Chris Jung, Georgy Noarav, Ramya Ramalingam, Aaron Roth. NeurIPS 2022.
Online Multivalid Learning: Means, Moments, and Prediction Intervals. Joint with Chris Jung, Georgy Noarav, Mallesh Pai, Aaron Roth. ITCS 2022.
Adaptive Machine Unlearning. Joint with Chris Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites. NeurIPS 2021.