I am an ML PhD student at CMU.
Currently, some of my interests include: LLM agents, inference-time compute, interpretability, and alignment.
I am very eager to meet other ambitious people! If you'd like to chat, please don't hesitate to get in touch.
I am an ML PhD student at Carnegie Mellon University advised by Yiming Yang. At a high level, my research aims to understand the ingredients for general intelligence while ensuring its safety.
As an undergrad at Cornell, I worked on LLM interpretability and truthfulness, and was a primary contributor to the papers Representation Engineering and Localizing Lying in Llama. I also worked at Gray Swan AI on adversarial robustness and evaluations. Previously, I did work in computational neuroscience, physics, and deep learning theory. I am also the creator of ProctorAI, AI-Timeline.org, and co-author of AidanBench.
Presented at NeurIPS 2024 Language Gamification Workshop
Summary: We benchmark the ability of models to come up with as many original answers as they can to open-ended questions.
Published front page of the Cornell Undergraduate Research Journal (CURJ)
Winner of the $300 James E. Rice Award
A literature review of learning algorithms and their biological plausibility
Proctor is a multimodal AI companion that watches your screen and yells at you if it sees you being unproductive. It has over 300 stars on Github.
I solved an "open question" posed in a previous paper by deriving this bound on the weights of a neural network. This was done in summer of 2021 during an REU at Johns Hopkins under Rene Vidal.
Improving the out-of-distribution robustness of BERT and GPT-2 by pretraining them to predict brain fMRI data.
A Spotify-like music player that operates from the command line. Gained over 140 stars on Github.
One of my great pleasures is meeting interesting and ambitious people! Please don't hesitate to reach out. I am often in Pittsburgh, New York, SF, and Berkeley.