Rongjie Lai

Rongjie Lai is a Professor in the Department of Mathematics at Purdue University, specializing in applied and computational mathematics. His work bridges geometric methods with machine learning, focusing on inverse problems, optimal transport, and manifold learning.

• Current research emphasizes data-driven modeling, mean-field games, and geometric understanding of non-Euclidean data.
• Organizer of key workshops and minisymposia at SIAM and IPAM conferences.
• Collaborates on NIH and NSF-funded projects, including protein NMR structure determination and variational mean-field theory.

His recent publications highlight geometric deep learning, adversarial training, and operator learning for complex systems. Former advisees include Bill Huang (Meta) and Jiajia Yu (Duke University).