ECE Colloquium - December 5
Dr. Trac D. Tran,
Johns Hopkins University
CoRE Building Lecture Hall
Most natural signals can be approximately represented by a few coefficients with respect to certain basis that carry the most relevant information. Processing of the signals in the sparsifying domain is much faster and simpler than in the original domain. This makes signal sparsity an extremely powerful tool in many classical signal processing applications. On the other hand, in many signal processing applications involving highly non-stationary signals such as images and videos, local adaptivity also plays a very important role in capturing the rich spatial/temporal/spectral correlation structure. In this talk, I will introduce the development of sparsity-constrained optimization algorithms based on content- or data-adaptive dictionary design for discriminative applications (detection, classification, and recognition). The proposed framework is applicable in a variety of practical discriminative applications, provided the assumption that signals lie in a union of low-dimensional subspaces holds.
I will particularly concentrate on target detection and classification for hyperspectral imagery. However, if time permits, I will also discuss other applications such as robust face recognition and other research directions in the area of sparse signal processing at Johns Hopkins.
Trac D. Tran S'94-M'98-SM'08 received the B.S. and M.S. degrees from the Massachusetts Institute of Technology, Cambridge, in 1993 and 1994, respectively, and the Ph.D. degree from the University of Wisconsin, Madison, in 1998, all in Electrical Engineering.
In July of 1998, Dr. Tran joined the Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, where he was recently promoted to the rank of Professor. His research interests are in the field of digital signal processing, particularly in sparse representation, sparse recovery, sampling, multi-rate systems, filter banks, transforms, wavelets, and their applications in signal analysis, compression, processing, and communications. His pioneering research on integer-coefficient transforms and pre-/post-filtering operators has been adopted as critical components of Microsoft Windows Media Video 9 and JPEG XR - the latest international still-image compression standard ISO/IEC 29199-2.
Dr. Tran was the co-director (with Prof. J. L. Prince) of the 33rd Annual Conference on Information Sciences and Systems (CISS'99), Baltimore, MD, in March 1999. In the summer of 2002, he was an ASEE/ONR Summer Faculty Research Fellow at the Naval Air Warfare Center & Weapons Division (NAWCWD) at China Lake, California. He is currently a regular consultant for the U.S. Army Research Laboratory in Adelphi, Maryland. Dr. Tran has served as Associate Editor of the IEEE Transactions on Signal Processing as well as IEEE Transactions on Image Processing. He was a former member of the IEEE Technical Committee on Signal Processing Theory and Methods (SPTM TC) and is a current member of the IEEE Image Video and Multidimensional Signal Processing (IVMSP) Technical Committee. He is currently serving his second term as an Associate Editor for IEEE Transactions on Signal Processing.
Prof. Tran received the NSF CAREER award in 2001, the William H. Huggins Excellence in Teaching Award from The Johns Hopkins University in 2007, and the Capers and Marion McDonald Award for Excellence in Mentoring and Advising in 2009.