I am a first-year PhD student advised by Tom Griffiths and Natalia Vélez in the AI & ML area of the Department of Computer Science at Princeton University. I am supported by the Gordon Y. S. Wu Fellowship in Engineering.
I study how humans share computation during collaborative tasks, taking inspiration from multiprocessing systems and computer architecture to formulate precise computational theories that can be tested on human behavioral data. Currently, I am interested in division of labor and how it can be related to parallel versus serial processing. When and how do groups of people parallelize tasks to effectively minimize time and energy usage? How do we maintain global task coherence when dividing subtasks amongst groups?
Before starting my PhD, I spent two years as a lab tech with Nancy Kanwisher at MIT, where I studied similarities and divergences between CNNs and visual representations in the human brain. I received my B.A. in Computer Science with a minor in Psychology from Cornell University in 2021, where I conducted research in autonomous navigation and natural language processing. In 2019 and 2020, I was a software engineering intern at The New York Times.
- Computational Models Recapitulate Key Signatures of Face, Body and Scene Processing in the FFA, EBA, and PPAJournal of Vision, 2022Publisher: The Association for Research in Vision and Ophthalmology