Wen-Yi Zhao received the doctoral degree in Electrical Engineering from University of Maryland, College Park in 2000. His PhD research was focused on robust face recognition. He studied electronic engineering with focus on image processing hardware at Tsinghua University, Beijing (BE degree in 1990); electrical engineering with focus on computer vision applications at University of Virginia (MS degree in 1995).

During 1990 to 1993, he worked for Huahuan Electronics Corporation Ltd. (a spin-off company from Tsinghua University), where he also advised undergraduates on their diploma projects. During 1997 to 1998, he visited LG Electronics Research Center of America, where he conducted research on video indexing and retrieval for the development of MPEG-7 standard. Since 2000, he has been working on various image processing, computer vision and pattern recognition problems at the Vision Technologies Lab of Sarnoff Corporation (formerly RCA Labs) in Princeton. In particular, he has worked on image/video enhancement including super-resolution, motion computation such as optical flow estimation and its application to tracking and surveillance, alignment of 2D-2D and 3D-3D data such as video-Lidar registration, camera pose estimation from images, biometrics such as iris recognition, and medical imaging such as image guided radiotherapy.

Wen-Yi has contributed two books, more than 35 book chapters, peer-reviewed journal and conference articles. He is the lead author of an influential ACM survey paper on face recognition (2003). He is a recipient of the best industry related paper award at the 17th International Conference on Pattern Recognition, 2004. Wen-Yi has been giving tutorials and invited talks on the subject of his expertise. He is a frequent reviewer for IEEE and other international journals and conferences. He has also been involved with organizing technical meetings. Wen-Yi is listed on Who’sWho in America (59th edition) and Who’sWho in Science and Engineering (8th edition).

 

Research Interests:

* Biometrics/Face Recognition
* Computer Vision and Image Analysis
* Pattern Recognition and Learning
* Multimedia/Signal and Image Processing
* Neuro imaging/Psychology on Object Perception
* Information Processing in Medical imaging