Elizabeth Mieczkowski
PhD Student @ Princeton CS
I am a second-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 Department of Defense National Defense Science and Engineering Graduate Fellowship (NDSEG) and the Gordon Y. S. Wu Fellowship in Engineering.
I study the optimal strategies underlying multi-agent collaboration by combining insights from cognitive science, large-scale multiplayer experiments, distributed computer systems, and multi-agent reinforcement learning. My research currently addresses two main questions: How can theories from distributed systems help us better understand the complex challenges and solutions that arise when dividing labor and resources during collaborative tasks? And how can these insights be used to improve the way that AI agents collaborate with people?
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.
Google Scholar // CV
selected publications
2024
- People Evaluate Idle Collaborators Based on their Impact on Task Efficiency2024
2023
- fROI-level computational models enable broad-scale experimental testing and expose key divergences between models and brainsJournal of Vision, Aug 2023