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Seminar Announcement

IEEE Signal Processing Society
Department of Electrical and Computer Engineering
University of Illinois at Chicago

 

Wednesday, November 30, 2016
12:30 p.m., 1000 SEO
851 S. Morgan St, Chicago, IL

Min Wu, Ph.D. 
Professor of ECE
Distinguished Scholar-Teacher
University of Maryland

 

“When Power Meets Multimedia”

Abstract: Osama bin Laden’s video propaganda prompted numerous information forensic questions: given a video under question, when and where was it shot? Was the sound track captured together at the same time/location as the visual, or superimposed later? Similar questions about the time, location, and integrity of multimedia and other sensor recordings are important to provide evidence and trust in journalism, crime solving, infrastructure monitoring, and other informational operations.

 

Although the R&D on power grid and multimedia signal processing did not seem to cross paths, an emerging line of research toward addressing the above questions exploits novel signatures induced by the power network. An example is the small random-like fluctuations of the electricity frequency known as the Electric Network Frequency (ENF), owing to the dynamic control process to match the electricity supplies with the demands in the grid. These signatures reflect the attributes and conditions of the power grid and become naturally “embedded” into various types of sensing signals. They carry time and location information and may facilitate integrity verification of the primary sensing data.

 

This talk will provide an overview of recent information forensics research on ENF carried out by our Media and Security Team (MAST) at University of Maryland, and discuss some on-going and open research issues.

 

Speaker’s Biography

Min Wu (minwu@umd.edu) is a Professor of Electrical and Computer Engineering and a Distinguished Scholar-Teacher at the University of Maryland, College Park. She received her Ph.D. degree in electrical engineering from Princeton University in 2001. At UMD, she leads the Media and Security Team (MAST), with main research interests on information security and forensics and multimedia signal processing. Her research and education have been recognized by a NSF CAREER award, a TR100 Young Innovator Award from the MIT Technology Review, an ONR Young Investigator Award, a Computer World "40 Under 40" IT Innovator Award, University of Maryland Invention of the Year Awards, an IEEE Mac Van Valkenburg Early Career Early Career Teaching Award, and several paper awards from IEEE SPS, ACM, and EURASIP. She was elected IEEE Fellow for contributions to multimedia security and forensics. Dr. Wu chaired the IEEE Technical Committee on Information Forensics and Security, and has served as Vice President - Finance of the IEEE Signal Processing Society and Founding Chief Editor of the IEEE SigPort initiative. Currently, she is serving as Editor-in-Chief of the IEEE Signal Processing Magazine and an IEEE Distinguished Lecturer. 

Website: http://www.ece.umd.edu/~minwu/

Hosts: Prof. Rashid Ansari, SPS Chicago Chapter Chair, ransari@uic.edu   

Prof. Mojtaba Soltanalian, SPS Chicago Chapter Vice Chair, msol@uic.edu

 

 

Wednesday, December 6, 2016

Refreshments & Reception 10:45 a.m.,Seminar 11:00 a.m.

SEO 1000, 851 South Morgan St., Chicago, IL 60607

 

Hamid Krim

Professor of ECE
North Carolina State University

 

“Convexity, Sparsity, Nullity and all that in Machine Learning”

Abstract: High dimensional data exhibit distinct properties compared to its low dimensional counterpart; this causes a common performance decrease and a formidable computational cost increase of traditional approaches. Novel methodologies are therefore needed to characterize data in high dimensional spaces.

 

Considering the parsimonious degrees of freedom of high dimensional data compared to its dimensionality, we study the union-of-subspaces (UoS) model, as a generalization of the linear subspace model. The UoS model preserves the simplicity of the linear subspace model, and enjoys the additional ability to address nonlinear data. We show a sufficient condition to use l1 minimization to reveal the underlying UoS structure, and further propose a bi-sparsity model (RoSure) as an effective algorithm, to recover the given data characterized by the UoS model from errors/corruptions.


As an interesting twist on the related problem of Dictionary Learning Problem, we discuss the sparse null space problem (SNS). Based on linear equality constraint, it first appeared in 1986 and has since inspired results, such as sparse basis pursuit, we investigate its relation to the analysis dictionary learning problem, and show that the SNS problem plays a central role, and may naturally be exploited to solve dictionary learning problems.
 

Substantiating examples are provided, and the application and performance of these approaches are demonstrated on a wide range of problems, such as face clustering and video segmentation.

 

Speaker’s Biography

 

Hamid Krim (ahk@ncsu.edu) received his BSc. MSc. and Ph.D. in Electrical Engineering. He was a Member of Technical Staff at AT&T Bell Labs, where he has conducted R&D in the areas of telephony and digital communication systems/ subsystems. Following an NSF postdoctoral fellowship at Foreign Centers of Excellence, LSS/University of Orsay, Paris, France, he joined the Laboratory for Information and Decision Systems, MIT, Cambridge, MA as a Research Scientist and where he was performing and supervising research.


He is presently Professor of Electrical Engineering in the ECE Department, North Carolina State University, Raleigh, leading the Vision, Information and Statistical Signal Theories and Applications group. His research interests are in statistical signal and image analysis and mathematical modeling with a keen emphasis on applied problems in classification and recognition using geometric and topological tools. He has served and is currently serving on the IEEE editorial board of SP, and the TCs of SPTM and Big Data Initiative, as well as an AE of the new IEEE Transactions on SP on Information Processing on Networks, and of the IEEE SP Magazine. He is also one of the 2015-2016 Distinguished Lecturers of the IEEE SP Society.

 

 

Hosts: Prof. Rashid Ansari, SPS Chicago Chapter Chair, ransari@uic.edu   

Prof. Mojtaba Soltanalian, SPS Chicago Chapter Vice Chair, msol@uic.edu

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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