Shih-Fu Chang


709 Schapiro CEPSR

Tel(212) 854-6894
Fax(212) 932-9421

Shih-Fu Chang's research is focused on computer vision, machine learning, and multimedia information retrieval. A primary goal of his work is to develop intelligent systems that can extract rich information from the vast amount of visual data including those emerging on the Web, collected through pervasive sensing, or available in gigantic archives. His work on content-based visual search in the early 90's set the foundation of this vibrant area. Over the years, he has developed innovative solutions for image/video recognition, multimodal analysis, multimedia ontology, image forensics, and compact hashing for large-scale search.

Research Interests

Computer Vision, Machine Learning, Artificial Intelligence, Multimedia Retrieval, Image Video Recognition, Multimedia Knowledge Extraction.

Chang’s work has had major impact on various applications like image/video search engines, online crime prevention, mobile search, AR/VR, and brain machine interfaces. His scholarly work can be seen in more than 350 peer-reviewed publications , best paper awards, more than 30 issued patents, and technologies licensed to companies. He was listed as the Most Influential Scholar in the field of Multimedia by Aminer in 2016. For his long-term contributions, he was awarded the IEEE Signal Processing Society Technical Achievement Award, ACM Multimedia Special Interest Group Technical Achievement Award, the Honorary Doctorate from the University of Amsterdam, and the IEEE Kiyo Tomiyasu Award. He received the Great Teacher Award from the Society of Columbia Graduates.

He served as Chair of ACM SIGMM (2013-2017), Chair of Columbia Electrical Engineering Department (2007-2010), the Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), and advisor for several institutions and companies. In his current capacity as Senior Executive Vice Dean of Columbia Engineering, he plays a key role in the School's strategic planning, special initiatives, international collaboration, and faculty development. 

He is a Fellow of the American Association for the Advancement of Science (AAAS), ACM, and IEEE.

Research Experience

  • Visiting faculty, Microsoft Research, Beijing, 2006
  • Visiting faculty, IBM T. J. Watson Research Center, 2004–2006

Professional Experience

  • Senior executive vice dean of engineering, Columbia University, 2015–
  • Senior vice dean of engineering, Columbia University, 2012–2015
  • Chief Technical Advisor, VidRovr Inc., 2016-
  • Chief Technical Advisor, Axon Image Inc., 2015-
  • Richard Dicker Chair Professor, Columbia University, 2011–
  • Professor of computer science, Columbia University, 2011–
  • Chair of electrical engineering, Columbia University 2007–2010
  • Professor of electrical engineering, Columbia University, 2002–2011
  • Associate professor of electrical engineering, Columbia University, 1997–2002
  • Assistant professor of electrical engineering, Columbia University, 1993–1997

Professional Affiliations

  • Fellow of the American Association for the Advancement of Science
  • Fellow of the Institute of Electrical and Electronics Engineers 
  • Fellow of Association of Computing Machinery (ACM)

Honors & Awards

  • Fellow, Association for Computing Machinery, 2017
  • Honorary Doctorate, University of Amsterdam, 2016
  • Most Influential Scholar in the Field of Multimedia, AMiner, 2016
  • Great Teacher Award, The Society of Columbia Graduates, 2013
  • Technical Achievement Award, IEEE Signal Processing Society, 2012
  • Technical Achievement Award, ACM Special Interest Group in Multimedia, 2011
  • Kiyo Tomiyasu Award, IEE, 2009
  • Young Investigator Award, Office of Naval Research, 1998–2001
  • Career Award, National Science Foundation, 1995–1998

Selected Publications

Liu, Wei, Jun Wang, Rongrong Ji, Yu‐Gang Jiang, and Shih‐Fu Chang. "Supervised hashing with kernels." In Computer Vision and Pattern Recognition (CVPR), IEEE Conference on, pp. 2074‐2081, 2012.

Wu, Xiao‐Ming, Zhenguo Li, Anthony M. So, John Wright, and Shih‐Fu Chang. "Learning with partially absorbing random walks." In Advances in Neural Information Processing Systems (NIPS), pp. 3077‐3085. 2012.

Wang, Jun, Tony Jebara, and Shih‐Fu Chang. "Semi-supervised learning using greedy max‐cut." Journal of Machine Learning Research 14, no. Mar (2013): 771‐800.

Ye, Guangnan, Yitong Li, Hongliang Xu, Dong Liu, and Shih‐Fu Chang. "Eventnet: A large scale structured concept library for complex event detection in video." In Proceedings of ACM international conference on Multimedia, pp. 471‐480. ACM, 2015.

Borth, Damian, Rongrong Ji, Tao Chen, Thomas Breuel, and Shih‐Fu Chang. "Large‐scale visual sentiment ontology and detectors using adjective noun pairs." In Proceedings of ACM international conference on Multimedia, pp. 223‐232. ACM, 2013.

Smith, John R., and Shih‐Fu Chang. "VisualSEEk: a fully automated content‐based image query system." In ACM international conference on Multimedia, pp. 87‐98. ACM, 1997.