I am a 3rd year CS PhD student at MIT CSAIL advised by Julie Shah, who co-advised my M.S. with Pulkit Agrawal. I spent a summer at Meta AI and two years as an AI Resident at Microsoft Research. I did my undergrad at Yale, where I played with robots with Brian Scassellati and read a lot of dead philosophers.

I’m interested in building agents that learn continuously from and with humans. To that end, I spend a lot of time thinking about how to align algorithmic representations with humans’, whether that be through designing novel learning algorithms or questioning the theoretical foundations of agency, goals, and planning. I get most excited by work that unifies RL, robotics, and cognitive science.

A history buff at heart, I care deeply about creating a world where AI is used safely, ethically, and equitably. I prioritize connecting with non-academic communities, and have worked at the White House Office of Science and Technology Policy (OSTP) and Schmidt Futures on AI policy. I also serve on the advisory board of the Yale Jackson School of Global Affairs, where I co-teach a course on AI for policymakers.

I love being outdoors, even in the brutal Boston winters. A current goal is to run a sub-3:00 marathon (this is how I’m doing). Reach out to chat about research, policy, or running! Preferred subject line: Your cat is dope.

email | cv | google scholar | twitter | linkedin


  • Ph.D. Computer Science, 2023 -

    Massachusetts Institute of Technology

  • M.S. Computer Science, 2023

    Massachusetts Institute of Technology

  • B.S. Cognitive Science, 2018

    Yale University

  • B.A. Global Affairs, 2018

    Yale University

People Financially Invested in My Future

  • Open Philanthropy
  • NSF Graduate Research Fellowship
  • Truman Scholarship
  • My parents

Recent News

All news»

[May 2023] I spoke alongside Congressman Bill Foster at the Aon AI Fireside Chat.

[May 2023] I gave a talk at the Yale for Humanity event on Artificial Intelligence, Ethics, and Society: Utilizing Technology for Good.

[Apr 2023] Our paper Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation was accepted to ICML 2023.

[Apr 2023] I ran the Boston Marathon!

[Mar 2023] Co-organizing Interactive Learning from Implicit Human Feedback workshop at ICML 2023.

[Feb 2023] Received my M.S. from MIT EECS.


Aligning Robot Representations with Humans
Investigations of Performance and Bias in Human-AI Teamwork in Hiring
Human-Machine Collaboration for Fast Land Cover Mapping
An Integrated Machine Learning Approach To Studying Terrorism
Conceptual Feasibility Study of the Hyperloop Vehicle for Next-Generation Transport
Early Detection of Boko Haram Attacks in Nigeria