Bir Bhanu

UC Riverside | Distinguished Professor


Lecture Information:
  • December 2, 2016
  • 2:00 PM
  • ECS 241
Bir Bhanu headshot

Speaker Bio

Dr. Bhanu is Bourns Presidential Chair and Distinguished Professor of Electrical and Computer Engineering at the University of California at Riverside (UCR). He serves as the Founding Director of the interdisciplinary Center for Research in Intelligent Systems (CRIS) since 1998 and the director of the Visualization and Intelligent Systems Laboratory (VISLab) since 1991. Currently he also serves as the Director of NSF IGERT Program on Video Bioinformatics and recently served as the Interim Chair of Department of Bioengineering (2014-2016). He was the founding faculty of Bourns College of Engineering and served as the founding Chair of Electrical Engineering from 1991-94 at UCR. Previously, he was a Senior Honeywell Fellow at Honeywell Inc. He has been on the faculty of the Department of Computer Science at the University of Utah and has worked at Ford Aerospace, INRIA-France, and IBM San Jose Research Laboratory. He has been the principal investigator of various programs for various agencies and industries in the areas of video networks, video understanding, video bioinformatics, learning and vision, image understanding, pattern recognition/data mining, target recognition, biometrics, navigation, image/video databases, and diverse applications. He has published extensively (10 books, over 500 reviewed technical publications, 145 journal papers, 54 book chapters) and holds 18 patents. He has received best conference papers and outstanding journal paper awards and the industrial and university awards for research excellence, outstanding contributions, team efforts and dissertation advisor/mentor. He has been the Chair of various conferences/workshops: IEEE CVPR, WACV, AVSS, ICDSC, and DARPA IUW. He received his EECS education at Massachusetts Institute of Technology and University of Southern California. Dr. Bhanu is a fellow of AAAS, IEEE, IAPR, SPIE and AIMBE.

Description

Modeling and recognizing the underlying dynamics of living entities at multiple spatio-temporal scales are challenging tasks. They provide a deeper understanding of dynamic processes related with detection, tracking, recognition, and characterization of behavior and occurrence of events. This talk will provide intelligent video systems from three domains: 1) video networks for human detection, tracking and recognition, 2) video bioinformatics for characterizing the health of cells and their growth and 3) video understanding of emotions for developing intelligent agents. It will present examples of new representations, indexing/matching and learning techniques for robust individual identification, re-identification, tracking; quality control of human embryonic stem cell colonies and applications in advertising.