A. Feder Cooper

À propos

My research develops metrics for ML capabilities, and makes sure that we can effectively and reliably measure these metrics at scale and in practice. My contributions span uncertainty estimation, privacy and security of generative-AI systems, distributed training, hyperparameter optimization, and model selection. I also do work in tech policy and law, and spend a lot of time finding ways to effectively communicate the capabilities and limits of AI/ML to interdisciplinary audiences and the public. Much of this work happens through The Center for Generative AI, Law, and Policy Research (GenLaw Center) (opens in new tab).

My work has received best paper accolades, spotlights, and oral presentation slots at several conferences, including ICML, AAAI, and NeurIPS.