A. Feder Cooper
Assistant Professor, Yale University
I research a variety of topics in reliable, scalable machine learning. My contributions span privacy, security, and evaluation of generative-AI systems, MLSys, and uncertainty estimation. 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.
I am recruiting Ph.D. students for Fall 2027. If you're getting in touch about a Ph.D., postdoc, or collaboration, please include a few sentences about a research paper you found interesting and why (it doesn't need to be one where I'm an author).
I'm an Assistant Professor of Computer Science at Yale University, where I'm also affiliated with the Information Society Project at Yale Law School, the Center for Algorithms, Data, and Market Design, and the Institute for Foundations of Data Science. I'm also an Affiliate Researcher at Stanford, working with Percy Liang, Dan Ho, and Mark Lemley, and a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard University.
My research has been awarded at NeurIPS, ICML, COLM, AAAI, and AIES, and has been covered in The Atlantic, The New York Times, The Washington Post, Bloomberg News, 404 Media, and Wired. Work on copyright and generative AI has been called "somewhat famous" by the popular press.