Gilad Lerman

Gilad Lerman is a Professor at the School of Mathematics, University of Minnesota, and serves as Director of the Data Science Lab at both the Minnesota Center for Industrial Mathematics (MCIM) and Institute for Mathematics and its Applications (IMA). His office is located at 533 Vincent Hall, 206 Church Street SE, Minneapolis, MN 55455.

Research Focus: Dr. Lerman specializes in computational harmonic analysis, high-dimensional data analysis, statistical learning, and machine learning. His work includes robust optimization techniques, non-convex modeling, and applications in computer vision and bioinformatics. Key methodologies involve geometric data analysis, variational methods, and spectral techniques for large-scale datasets.

Publications: His recent works demonstrate consistent focus on robust machine learning, including subspace recovery, Riemannian data assimilation, graph neural networks, and applications in geophysics/computer vision. Theoretical rigor combines with practical implementations across domains.

Student Advising & Grants: He has supervised 16+ PhD dissertations and 3 MSc theses, with graduates now in academia and industry (Google, NVIDIA, Mayo Clinic). Current research is supported by NSF and NGA funding.

Laboratory Leadership: Directs the IMA Data Science Lab, focusing on industrial mathematics collaborations and developing algorithms for real-world data challenges.