Curriculum Vitae


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Cheng-en (Charles) Guo

Office: BH 3532F, Computer Science Dept.

             University of California, Los Angeles

Tel: (310) 206-7372(o), (310) 397-5649(h)

URL: http://www.cs.ucla.edu/~cguo

Address: 3340 Sawtelle Blvd., Apt. 202

                Los Angeles, CA 90066

Fax: (310) 206-5658

Email: cguo@cs.ucla.edu


Research Interests

Computer Vision, Machine Learning, Statistical Modeling and Computing, Image/Video Processing, Image/Video Compression, Bayesian Inference, Pattern Recognition, Computer Graphics, Human-Computer Interaction, Visual Art, etc. etc.

Education

·   Ph.D.

Computer Science Dept., University of California, Los Angeles, June 2004

Thesis: “A Mathematical Theory of Textons and Primal Sketch

Advisor: Prof. Song-Chun Zhu.

·   M.S.

Institute of Automation, Chinese Academy of Sciences, China, June 1998.

·   B.E.

Double Major with Honors, Mechanical & Computer Engineering,

Tsinghua University, China, July 1995.

 

Professional Experiences

·  Sep. 2002 present

Research Assistant, Center for Image and Vision Science, UCLA.

·  Nov. 2003 – Jan. 2004   Intern, Microsoft Research Asia, Beijing, China.

·  Jun. 2001 – Aug. 2001

Intern, Kodak Research Lab, Rochester, NY.

·  Jul. 1999 – Aug. 2002

Research Assistant, OSU Vision and Learning Lab, Ohio State Univ.

·  Jun. 1998 – Jun. 1999

Research Assistant, Non-Destructive Evaluation Lab, Ohio State Univ.

·  Sep. 1995 – Jun. 1998

Research Assistant, Artificial Intelligence Lab

Institute of Automation, Chinese Academy of Sciences.

·  Jul. 1994 – Jul. 1998

Research Assistant, Robotics Lab, Tsinghua Univ., China.

 

Membership and Awards

·   Current

Student member of IEEE, IEEE Computer Society, and ACM.

·   2001-2002

Member of Phi Kappa Phi.

·   2000-2002

Member of Upsilon Pi Epsilon.

·   1996-1998

Excellent Graduate Student Scholarship, Institute of Automation, China.

·   1995

Graduate with Honors, Tsinghua University, China.

·   1990-1995

1st class Scholarship, “JiangNanXiang” and “12.9” scholarships, Tsinghua.

 

Publications (All papers are available at http://www.cs.ucla.edu/~cguo)

Journal Articles:

1.      Cheng-en Guo, Song-Chun Zhu, and Ying Nian Wu,

“Modeling Visual Patterns by Integrating Descriptive and Generative Methods”,  

International Journal of Computer Vision, Vol. 53, No. 1, pp.5-29, June 2003.

2.      Jiebo Luo and Cheng-en Guo,

 “Perceptual Grouping of Segmented Regions in Color Images”,

Pattern Recognition, vol. 36, no. 12, pp.2781-2792, December 2003.

3.      Song-Chun Zhu, Cheng-en Guo, Yizhou Wang, and Zijian Xu,

“What are Textons?”,

International Journal of Computer Vision (accepted).

Conference Articles:

4.      Cheng-en Guo, Ying Nian Wu, and Song-Chun Zhu,

“Scaling Laws on Complexity and Perceptibility”, submitted.

5.      Cheng-en Guo, Song-Chun Zhu and Ying Nian Wu,

“A Mathematical Theory of Primal Sketch and Sketchability”,

Proc. of 9th International Conference on Computer Vision, pp.1228-1235, Nice France, 2003.

6.      Song-chun Zhu, Cheng-en Guo, Ying Nian Wu and Yizhou Wang,

“What are Textons?”,

Proc. of 7th European Conf. on Computer Vision, pp.793-807, Copenhagen, Denmark, 2002.

7.      Ying Nian Wu, Song-Chun Zhu and Cheng-en Guo,

“Statistical Modeling of Image Sketch”,

Proc. of 7th European Conf. on Computer Vision, pp.240-254, Copenhagen, Denmark, 2002.

8.      Jiebo Luo and Cheng-en Guo,

“Non-Purposive Perceptual Region Grouping”,

Proc. of IEEE Int’l Conf. on Image Processing, vol.2, pp.749-752, Rochester, NY 2002.

9.      Cheng-en Guo, Song-Chun Zhu and Ying Nian Wu,

“Visual Learning by Integrating Descriptive and Generative Models”,

Proc. of 8th Int’l Conf. on Computer Vision, vol.1 pp. 370-377, Vancouver, Canada, 2001.

10.   Song-Chun Zhu and Cheng-en Guo,

“Conceptualization and Modeling of Visual Patterns - A Modern Statistical Physics Foundation for Visual Complexity”,

Proc. of Third Workshop on Perceptual Organization in Computer Vision, Vancouver, Canada, 2001.

11.   Song-Chun Zhu and Cheng-en Guo,

“Mathematical Modeling of Clutter: descriptive vs. generative models”,

Proc. of SPIE AeroSense Conf. on Automatic Target Recognition, Orlando, FL. 2000.

 

Invited Talks

1.      Joint Statistical Meeting (JSM), San Francisco, CA, August 2003

2.      Research Review, Computer Science Dept., UCLA, April 2003

3.      Joint Statistical Meeting (JSM), New York, NY, August 2002

4.      First SIAM (Society for Industrial and Applied Mathematics) conference on Image Science, Boston, MA, March 2002

 

Status

Permanent Residence of US (pending, work permit and advance parole approved).

 

References:

 

Prof. Song-Chun Zhu

Department of Statistics and Computer Science

University of California, Los Angeles

Address: 8130 Math Science Building

               Box 951554,
               University of California, Los Angeles
               Los Angeles, CA 90095

Email:    sczhu@stat.ucla.edu

Tel:        310-206-8693

Fax:       310-206-5658

           

Prof. Ying Nian Wu

Department of Statistics and Computer Science

University of California, Los Angeles

Address: 8130 Math Science Building

               Box 951554,
               University of California, Los Angeles
               Los Angeles, CA 90095

Email:    ywu@stat.ucla.edu

Tel:        310-794-4860

Fax:       310-206-5658

 

Prof. Alan L. Yuille
Department Statistics and Psychology
University of California, Los Angeles

Address: 8130 Math Science Building

               Box 951554,
               University of California, Los Angeles
               Los Angeles, CA 90095

Email:    yuille@stat.ucla.edu

Tel:        310-267-5383
Fax:       310-206-5895

Dr. Jiebo Luo

Senior Principal Scientist

Image Science Technology Lab

Kodak Research Laboratories

Eastman Kodak Company

Address: 1700 Dewey Avenue

               Rochester, NY 14650-1816

Email:    luo@image.kodak.com

Tel:       585-722-7139

Fax:      585-722-0160

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This page was last updated: Wednesday February 04, 2004 . © Cheng-en Guo 2002-2003