Qiang Ji is a Professor of Electrical Engineering at Rensselaer Polytechnic Institute. He received his PhD in Electrical Engineering from the University of Washington in 1998. His research focuses on computer vision, probabilistic machine learning and their applications. He has extensive experience in developing computer vision techniques for real time and non-intrusive driver state/behavior analysis, recognition, and assistance. He has published over 230 papers in these areas. His research has been supported by major governmental agencies including DOT, FHWA, NSF, and DoD. Besides IEEE ITS, he also serves as an associate editor for IEEE Transactions on Affective Computing, IEEE Transactions on Cybernetics, and as a general chair or program chair for numerous international conferences/workshops. He previously served as a program director at the National Science Foundation, responsible for NSF computer vision and machine learning program, and as a member of the National Academics of Sciences? Safety Technical Expert Task Group (T-ETG) on Computer Vision, overseeing the processing and analysis of the SHRP 2 Naturalistic Driving data. He is a fellow of the IEEE and a fellow of the International Association of Pattern Recognition (IAPR).
1. Computer vision & Real-Time Image Analysis 2. Driver State and Intent Recognition 3. Advanced Driver Assistance Systems (expert systems, intelligent agents) 4. Vision-based Autonomous vehicle