A. Feder Cooper

Gates Hall
Department of Computer Science
Cornell University
afc78 [AT] cornell [DOT] edu

arxiv scholar
A. Feder Cooper

I am a scalable machine-learning researcher who does work at the intersection of computer science and law. Currently, I am a CS Ph.D. candidate at Cornell University, an Affiliate at the Berkman Klein Center for Internet & Society at Harvard University, a lead co-organizer of GenLaw, and an incoming student researcher at Google AI Research.

My Ph.D. work centers on how to make more reliable conclusions when using machine-learning methods at scale and in practice. My contributions span distributed training, hyperparameter optimization, uncertainty estimation, model selection, and generative AI (in particular, open and scalable text-to-image modeling). I engage in related research in tech policy and law, for which I also spend a lot of time working to effectively communicate the capabilities and limits of machine learning to a wider audience.

In the past I interned at Microsoft Research and was named a "Rising Star in EECS" by MIT. I am also an alum of Cornell's initiative on Artificial Intelligence, Policy, and Practice (AIPP), which has very generously supported my work through funding from the John T. and Catherine D. MacArthur Foundation.

Prior to my research career, I worked for several years as a software engineer at companies both (really) big and (really) small. I specialized in designing, building, and monitoring large-scale backend data-processing systems.

Selected papers and blog posts

*Equal contribution