I am a final-year PhD student at MIT EECS, where I am advised by Aleksander Mądry. Before starting my PhD, I spent two great years at Microsoft Research, where I worked with Praneeth Netrapalli and Prateek Jain. I received my BS in CS and Stats from the University of Illinois at Urbana-Champaign and have interned at Google Research, Apple MLR, and Akuna Capital.

I am interested in understanding and steering large-scale machine learning models. My recent work focuses on developing tools for analyzing model behavior via targeted interventions to learning algorithms, training data, in-context information, and learned representations. Outside of research, I enjoy cricket and tennis.

[Update] I'm on the job market for research positions in industry!


Papers

Parameters vs FLOPs: Scaling Laws for Optimal Sparsity of MoE Language Models
ContextCite: Attributing Model Generation to Context
Decomposing and Editing Predictions by Modeling Model Computation
ModelDiff: A Framework for Comparing Learning Algorithms
Do Input Gradients Highlight Discriminative Features?
The Pitfalls of Simplicity Bias in Neural Networks
Growing Attributed Networks through Local Processes

Blog posts