Yijiang Li

Yijiang Li is an Assistant Computational Mathematician in the Mathematics and Computer Science Division at Argonne National Laboratory. His research develops distributed optimization methods for large-scale scientific machine learning, spanning federated learning across HPC facilities, efficient training and compression of large language models, and AI for energy systems. He is a developer of APPFL, an open-source framework for privacy-preserving federated learning, and his work has appeared in ICML, NeurIPS, NAACL, and KDD. He received his PhD in Operations Research from the Georgia Institute of Technology in 2023.