ATS Seminar Series: Hairong Qi
The Advanced Technologies Section (ATS) of the National Center for Computational Sciences at ORNL is a world leader in developing and deploying scientific and technical solutions for leadership-class computing environments. The R&D activities of ATS are organized around designing and deploying leadership class systems, developing artificial intelligence solutions for science and smart facilities of the future, and stewardship of data and workflows at scale to enable science. The ATS Seminar Series is a forum for learning from experts and engaging with collaborators to advance their scientific mission.
Physics-based Learning: Formulation and Applications
Deep learning models have achieved tremendous success but often need large amount of training data which might not be readily available. This talk explores physics-based learning framework to largely reduce its dependency on large training benchmark, providing a more explainable and robust learning alternative. The talk will discuss different approaches to extract physical dynamics from the data and to embed physical constraints to the learning process. Applications like style transfer, cross-domain classification, and super resolution will be discussed to showcase the physics-based learning outcome.
Associate Department Head,
Min H. Kao Department of Electrical
Engineering and Computer Science
Tickle College of Engineering
University of Tennessee
Hairong Qi received the B.S. and M.S. degrees in computer science from Northern JiaoTong University, Beijing, China in 1992 and 1995, respectively, and the Ph.D. degree in computer engineering from North Carolina State University, Raleigh, in 1999. She is currently the Gonzalez Family Professor with the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. Her research interests are in the general areas of computer vision and machine learning. Dr. Qi’s research is supported by National Science Foundation, DARPA, IARPA, Office of Naval Research, NASA, Department of Homeland Security, etc. Dr. Qi is the recipient of the NSF CAREER Award. She is awarded the Highest Impact Paper from the IEEE Geoscience and Remote Sensing Society in 2012. Dr. Qi has published over 200 technical papers in archival journals and refereed conference proceedings, including two co-authored books with Dr. Wesley Snyder in Computer Vision. Dr. Qi is an IEEE Fellow.
Vimeo link: https://vimeo.com/698626710
Hairong Qi Associate Department Head, Min H. Kao Department of Electrical Engineering and Computer Science Tickle College of Engineering University of TennesseeHairong QiAssociate Department Head, Min H. Kao Department of Electrical Engineering and Computer Science Tickle College of Engineering University of Tennessee