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 (ML) researcher, working on reliable measurement and evaluation of ML and ML systems. 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 organizer of GenLaw, and an incoming student researcher at Google AI Research.

My research involves coming up with nuanced quality metrics for ML behaviors, and making sure that we can effectively measure these metrics at scale and in practice. My contributions span distributed training, hyperparameter optimization, uncertainty estimation, model selection, and generative modeling. To make sure that our evaluation metrics can meaningfully measure what we want ML to do in the world, I engage in related research in tech policy and law. 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. My work has been generously supported by the John T. and Catherine D. MacArthur Foundation through Cornell AIPP.

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 work

*Equal contribution; full list available here