Computational Biology Seminar Series for Undergraduates

Sponsored by the Department of Biological Sciences and the Center for Computation & Technology

Geometric Data Matching for Computational Forensics and Biomedical Imaging

Abstract:

To compute geometric data matching is to establish bijective correspondence between 3D objects/regions or images. Effective matching computation could facilitate the identification of specific patterns, detection of similarities, and tracking/understanding of data’s deformation and its trend. Therefore, it has broad applications in many scientific data processing tasks. We will briefly introduce a set of geometric matching algorithms developed in LSU Geometric and Visual Computing group and show their applications in computational forensics and biomedical imaging.

Bio:

Xin Li is the Oskar R. Menton associate professor at LSU, jointly in the School of Electrical Engineering and Computer Science (EECS) and the Center for Computation and Technology (CCT). He is also an adjunct faculty member at Pennington Biomedical Research Center. He got his Ph.D. in computer science from State University of New York at Stony Brook in 2008. He leads the LSU Geometric and Visual Computing (GVC) group. His research interests are on computer graphics and vision, spatiotemporal geometric data modeling and processing, image processing, and visualization. He also actively collaborates with domain scientists to develop geometric and visual data computing techniques for various scientific tasks in computational forensics, biomedical imaging, robotics, computer-aided design/manufacturing, coastal modeling and simulation, etc.

Xin (Shane) Li

LSU School of Electrical Engineering & Computer Science and Center for Computation & Technology

Associate Professor