Daphne Cornelisse
Hello! I am a second-year Ph.D. student at NYU, supervised by Professor Eugene Vinitsky. My research centers on developing effective and human-compatible agents. More concretely, I currently focus on two areas: 1) Controllable behavior generation, where I combine data-driven and mechanistic approaches to model human behavior and design reliable evaluation protocols; and 2) Adaptation, where I aim to understand the ingredients that enable agents to flexibly and safely adjust to unseen multi-agent settings.
Outside the lab, I enjoy boxing, going for a run along the East River, reading, and sketching.
Google Scholar / GitHub / Twitter / Goodreads
News
Oct 2024. Talk: Gave an invited talk on HR-PPO and GPUDrive at the RL reading group at UoE! The 📽️ recording is found here.
May 2024. Paper: Human-compatible driving partners through data-regularized self-play reinforcement learning was accepted to RLC 2024.
Apr 2024. Talk: Gave an invited talk on Human-Regularized PPO at the Berkeley Multiagent Learning Seminar! The slides are here.
Sep 2023: Started my Ph.D. at NYU with the EMERGE Lab!
Papers
Neural payoff machines: predicting fair and stable payoff allocations among team members
Daphne Cornelisse, Thomas Rood, Mateusz Malinowski, Yoram Bachrach, Tal Kachman
NeurIPS 2022
Paper | Poster | Tweet | Master thesis