Guangliang Chen

Guangliang Chen is an Associate Professor in the Department of Mathematics and Statistics at San José State University (SJSU), part of the College of Science. His research focuses on subspace/manifold clustering, dictionary learning, and classification with applications in image and document analysis. He earned a Ph.D. in Applied Mathematics from the University of Minnesota (2009) and a B.S. in Mathematics from the University of Science and Technology of China (2003).

Key research contributions include scalable spectral clustering algorithms, geometric multi-resolution analysis, and advancements in compressive sensing. His work has been recognized with a Best Paper Award at the 2009 ICCV workshop for Kernel Spectral Curvature Clustering (KSCC). He teaches courses in applied statistics, machine learning, and data visualization at both undergraduate and graduate levels.

Dr. Chen's recent projects involve developing efficient SVM classification techniques, large-scale spectral clustering frameworks, and MATLAB implementations for scalable algorithms. His research also extends to anomaly detection in hyperspectral imaging and functional genomics analysis through multiscale methods.