Deep Learning for 3D Scene Modeling & AI-Enhanced Healthcare (Feb 20)

Date: Feb 20, 11:45 – 12:45 pm

Abstract:

3D scene modeling is fundamental in many applications including Virtual Reality, Augmented Reality, Autonomous Driving, Robotics, Telehealth, etc. In this talk, I will first discuss some of our recent works in 3D scene modeling including: 1) PanoDepth: a deep learning based omnidirectional depth estimation framework via a novel integration of multi-scale view synthesis and multi-view stereo matching; and 2) OmniFusion: a 360 monocular depth estimation framework via geometry-aware fusion. I will then describe some of our ongoing projects in AI-enhanced healthcare including 3D face recognition and 3D brain imaging for autism subgroup phenotyping and genotyping, digital pathology, and 3D multi-organ segmentation to support Stereotactic MRI guided online Adaptive Radiotherapy (SMART), etc.

Biographical Sketch

Andy Duan is a Program Director in the Directorate for Computer and Information Science and Engineering (CISE) at the National Science Foundation (NSF) and a Professor in the School of Computing at Clemson University. Andy received his B.S. in Mathematics from Peking University in 1991, his M.S. in Mathematics in Utah State University in 1996, and his M.S. and Ph.D. in Computer Science from the State University of New York at Stony Brook in 1998 and 2003, respectively. His research interests include Computer Vision, Machine Learning, Computer Graphics, Virtual Reality and Biomedical Imaging, etc. He was the recipients of the Department of Defense Autism Concept Award, the Brain and Behavior Research Foundation Young Investigator Award, the Best Paper Honorable Mentioning Award at IEEE Visualization Conference, and the Editor’s Choice Award of the Journal of Medical Physics, etc. He was the Workshop Chair for IEEE Workshop on Bioinformatics in Biomedical Imaging in 2013 and the Conference Chairs of the IEEE International Conference on Shape Modeling (SMI) in 2018 and 2019.

Location: LOV 353 and ZOOM