I am a fourth year Ph.D. student at Carnegie Mellon University advised by Giulia Fanti. My main research interest is in Federated Learning (FL). I like to think about finding solutions to problems that plague FL in production use cases while still protecting user privacy. Outside of FL, I am broadly interested in (and have experience working on) self-supervised learning, representation learning, learning-to-rank (ranking), NLP, CV, transformer models, deep learning, and optimization.

Before I started at CMU, I did my undergrad at Princeton University, where I worked with Yuxin Chen and Miklos Racz.

Google Scholar, Github, LinkedIn, CV

Contact me at [charlieh at andrew dot cmu dot edu].