Electrical Engineering Manager

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Hawthorne, NY

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November 23, 2012

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Lexing Xie

IBM T. J. Watson Research Center

19 Skyline Dr.

Hawthorne, NY 10532

914-***-**** (office)

212-***-**** (home)

xlx @ ee.columbia.edu

EDUCATION Columbia University, New York, NY (September 2000- August 2005).

Ph.D., Electrical Engineering (August 2005)

Thesis Title: Unsupervised Pattern Discovery for Multimedia Sequences

Thesis Advisor: Prof. Shih-Fu Chang

M. Phil., Electrical Engineering, May 2004.

M.S., Electrical Engineering, December 2001, GPA 4.15/4.00

Tsinghua University, Beijing, China (September 1996 - June 2000).

B.S. with Honors, Dept. of Electronic Engineering, June 2000.

RESEARCH AND

TEACHING

EXPERIENCES

IBM T. J. Watson Research Center, Hawthorne, NY.

Research Staff Member, January 2007 -

Josef Raviv Memorial Postdoctoral Fellow, October 2005 December 2006

Multimedia Research group, Business Informatics Department

Research on multimedia content analysis and mining, resulted in multiple publications, patent

applications and one best student paper award. Topics include:

square4 Multimedia search and retrieval

square4 Event detection and pattern mining in multimedia

square4 Social context for media annotation

square4 Systems and large-scale applications in multimedia indexing and recognition

Columbia University, New York, NY.

Adjunct Assistant Professor, Dept. of Electrical Engineering, January 2007-May 2008

square4 Co-teach graduate seminar EE 6882 Statistical Video Analysis and Indexing, with Shih-Fu

Chang, Fall 2007.

square4 Co-teach graduate class EE 4830 Digital Image Processing, with Shahram Ebadollahi, Spring

2007 and 2008.

Columbia University, New York, NY.

Graduate Research Assistant, Digital Video and Multimedia Lab, Dept. of Electrical Engineering

September 2000-August 2005 Advisor: Prof. Shih-Fu Chang

Research Experience:

square4 Research on multimedia analysis, structure discovery and summarization, resulting in eleven

publications, two patents and three best student paper awards.

Teaching Experience:

square4 Teaching assistant / course manager for three courses: EE6880 Statistical Methods for Video

Indexing and Analysis (Fall 2003, graduate seminar), EE4830 Digital Image Processing

(Spring 2001, Summer 2001 and 2002, senior undergraduate / graduate), EE3203 Signals and

Systems II (Fall 2000, undergraduate). Resulted in three excellent TA awards from the School

of Engineering and Applied Science, Columbia University.

Microsoft Research, Cambridge, UK.

Research Intern, June August 2003. Manager: Dr. Patrick P rez, Dr. Andrew Blake

square4 Tackled the problem of object class recognition from images, devised semi-supervised

learning techniques for learning a part-based object appearance model.

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Related Contentsvised PatternDiscovery for Multimedia Sequences Lexing Xie Submitted in partial fulflllment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences Columbialy on visualanalysis and statistical machine learning methods [1,2,6]. Our approach to search and retrieval leverages such concept models to Query Execution Model-based re-ranking of shots ConceptMellon University, Research in the CMU speech group, 1984 - 1992. Research concentrated on speech interfaces, parsing and grammars for speech recognition. Also worked on a knowledge-based machine translationdynamic knowledge, context, reasoning, learning, MediaNet, MPEG-7 1. NEED FOR INTELLIGENCE IN CONTENT-BASED RETRIEVAL Recent research on the analysis of audio-visual content has enabled a firstfor the analysis of sound mixtures in the context of automatic multimedia scene analysis. In comparison with video and image anal- ysis, there has been little work on the general problem of organizing everydayTEXT AND AUDIO-VISUAL FEATURES IN VIDEO INDEXING Shih-Fu Chang1, R. Manmatha2, and Tat-Seng Chua3 1 Department of Electrical Engineering, Columbia University 2 Department of Computer Science, University

ComputerVisionStory [Compatibility Mode]

1 Computer Vision Story Mubarak Shah Computer Vision Computer Vision deals with recovery and f i f ti b t bj t t iuse o n orma on a ou o ec s presen n a scene from images of the scene. Mellon UniversityDigitalVideoResearch Evaluation and User Studies with Respect to Video Summarization and Browsing Computer Engineering, Michigan State University, 03/05. 3. Distinguished Achievement Award, College of Engineering, University of Michigan, 03/01. 4. Barbour Scholar, Rackham School of Graduate StudiesKeywords Video on Demand, Interactive Video, Video Interoperability, Video Servers, MPEG-2 Video over ATM, Internet Video 1. Introduction At Columbia University, we are developing a VoD testbed with advancedColumbia University, NY IBM T. J. Watson Research Center, NY >> icassp 2004, accepted ABSTRACT In this paper, we present our new results in news video story seg- mentation and classification in the contextCopyright 2007 ACM 978-1-59593-701-8/07/0009 5.00. Result-Based Expansion (map results to Database Management Systems at Journal of Visual Communication and Image Representation, 2004. Correspondence Contact: Prof. Shih-Fu Chang Department of ElectricalComputer Engineering and Center for Visualization & Virtual Environments, University of Kentucky (UK). Adjunct faculty, Joint Institute of University of Michigan-Shanghai Jiao Tong University (UM-SJTU)based imagesearch engines were also optimized for better performance. 1.3 Manual search Our manual search runs exploited multiple retrieval agents in the dimensions of color, texture, ASR, OCR, Columbia University, New York Graduate research assistant, High Level Vision Lab Advisor: Professor John Kender Analysis, indexing and enhancement of unstructured videos of presentations based on textuals for analysis and semantic modeling of visual content as part of the IBMMultimediaAnalysis and Retrieval Sys- tem (IMARS). We used this as a foundation in terms of providing a starting set of visualSouth University Changsha, China B.E. in Computer Science and Engineering July 1996 Graduated with honors RESEARCH INTERESTS My research interests lie in natural language processing, machine translationIndexing of Multimedia Content Using Visual, Audio, and Text Cues W. H. Adams IBM Thomas J. Watson Research Center, Yorktown Heights, NY 10598, USA Email: *******@**.***.*** Giridharan Iyengar IBM Thomas J.Hopkins University (Psychology, French Minor) 1982 EMPLOYMENT Carnegie Mellon University (Pittsburgh, PA), Senior System Scientist, School of Computer Science, 1998 - present. System Scientist, SchoolRecommended Courses

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