My name is Chris Watson and I'm a fourth year Ph.D. student at the University of Pennsylvania, where I am very fortunate to be advised by Rajeev Alur and Dinesh Jayaraman. I am very interested in (and currently working on!) integrating logical specifications, machine perception, and reinforcement learning to synthesize control policies for long horizon tasks.
I am a proud member of Penn's PLClub and the ASSET center (where I was recently featured in an article that describes our goal of safe, explainable, and trustworthy AI!). During Summer 2024, I interned at the NASA Ames research center, where I started collaborating with Corina Păsăreanu and Divya Gopinath. We are working on the (very interesting!) problem of getting system-level safety guarantees for autonomous systems that use high-dimensional perception.
A Robust Theory of Series-Parallel Graphs. Rajeev Alur, Caleb Stanford, and Christopher Watson. POPL 2023.
Stream Types. Joseph W. Cutler, Christopher Watson, Emeka Nkurumeh, Phillip Hilliard, Harrison Goldstein, Caleb Stanford, Benjamin C. Pierce. PLDI 2024.
Illustrated Landmark Graphs for Long-horizon Policy Learning. Christopher Watson, Arjun Krishna, Rajeev Alur, and Dinesh Jayaraman. LEAP @ CORL 2024 (workshop poster).
CS 4810: Introduction to Theory of Computing. Cornell University. Fall 2019.
CIS 5110: Theory of Computation. University of Pennsylvania. Fall 2022.
CIS 6730: Computer-Aided Verification. University of Pennsylvania. Spring 2023.
I've had the pleasure of being a student volunteer at POPL'22 and CCC'22, and of being a student at SSFT'22 and OPLSS'22.
ccwatson at seas dot upenn dot edu