Shih-Fu Chang

Last updated
Shih-Fu Chang
張世富
Born
Yunlin, Taiwan
Alma mater National Taiwan University (BS)
University of California, Berkeley (MS, PhD)
Awards
Scientific career
Fields Computer science, electrical engineering
Institutions Columbia University
Website www.ee.columbia.edu/~sfchang

Shih-Fu Chang is a Taiwanese American computer scientist and electrical engineer noted for his research on multimedia information retrieval, computer vision, machine learning, and signal processing.

Contents

Chang is currently the dean of the School of Engineering and Applied Science of Columbia University, where he is also the Morris A. and Alma Schapiro Professor. He served as the chair of the Special Interest Group of Multimedia (SIGMM) of Association for Computing Machinery (ACM) from 2013 to 2017. He was ranked as the Most Influential Scholar in the field of Multimedia by Aminer in 2016. [1] He was elected as an ACM Fellow in 2017. [2]

Biography

Chang received a bachelor of science in electrical engineering from National Taiwan University in 1985. He received a master of science and a doctor of philosophy in electrical engineering and computer science from the University of California, Berkeley in 1991 and in 1993, respectively. [3]

After receiving his doctorate degree, he joined Columbia University as an assistant professor. He served as the Chair of Electrical Engineering from 2007 to 2010 and received joint appointment in Computer Science in 2011. He served as a co-PI and later as Co-Director of Columbia University’s ADVENT Industry Consortium, which includes more than 25 industry sponsors in the area of media technologies, from 1993 to 2003. He became the Senior Vice Dean (2012-2015) and later Senior Executive Vice Dean (2015-2022) of Columbia's Engineering School, assuming a major role in the School’s efforts in Strategic Planning, Special Research Initiatives, Faculty Development, and International Collaboration. He is currently the dean of Columbia School of Engineering and Applied Science. Chang is noted for his influential work in multimedia information retrieval, with broad applications in large-scale image/video search, mobile visual search, image authentication, and information retrieval with semi-supervised learning. His research has resulted in more than 10 technology licenses to companies and the creation of three startup companies. As of January 2023, his publications have been cited more than 67,000 times with an h-index of 130. [4]

Awards

Chang’s notable awards include:

Research

Chang’s research includes multimedia information retrieval, computer vision, machine learning, and signal processing. The primary focus of his work is on development of intelligent methods and systems for extracting information from visual content and multimedia that are prevalent in large archives and live sources. In the early 1990s, his group developed some of the earliest and best-known content-based image search systems, VisualSEEk and VideoQ, [7] [8] which set the foundation of this vibrant area. During last two decades, he has made significant contributions to the field of multimedia retrieval by developing large multimedia ontologies, large libraries of visual concept classifiers, and automatic methods for multimedia ontology construction. [9] [10] [11] [12] These have strongly influenced design of the video search systems used in practice today. [13] He has developed several well-known compact hashing techniques [14] for efficient search over billion-scale image databases. His compact hashing work has enabled order of magnitude speedup and storage reduction in high-profile applications such as an online human trafficking crime fighting system (joint work with Svebor Karaman) that has been deployed in 200+ law enforcement agencies. [15] [16] In addition, he has developed a series of fundamental methods of graph-based semi-supervised learning [17] [18] that successfully address the challenge of training large-scale multimedia retrieval systems with noisy and sparse labels. These methods have been adopted in building the first commercialized brain machine interface system [19] for rapid image retrieval. The graph-based search process, based on the random walk with restart theory, developed jointly with X. Wu and Z. Li, has also been deployed in the large app recommendation system of Huawei (more than 300 million users). [18]

Related Research Articles

<span class="mw-page-title-main">Content-based image retrieval</span> Method of image retrieval

Content-based image retrieval, also known as query by image content (QBIC) and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases. Content-based image retrieval is opposed to traditional concept-based approaches.

<span class="mw-page-title-main">Automatic image annotation</span>

Automatic image annotation is the process by which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. This application of computer vision techniques is used in image retrieval systems to organize and locate images of interest from a database.

<span class="mw-page-title-main">Thomas Huang</span> Chinese-American engineer and computer scientist (1936–2020)

Thomas Shi-Tao Huang was a Chinese-born American computer scientist, electrical engineer, and writer. He was a researcher and professor emeritus at the University of Illinois at Urbana-Champaign (UIUC). Huang was one of the leading figures in computer vision, pattern recognition and human computer interaction.

Michael S. Lew is a scientist in multimedia information search and retrieval at Leiden University, Netherlands. He has published over a dozen books and 150 scientific articles in the areas of content based image retrieval, computer vision, and deep learning. Notably, he had the most cited paper in the ACM Transactions on Multimedia, one of the top 10 most cited articles in the history of the ACM SIGMM, and the most cited article from the ACM International Conference on Multimedia Information Retrieval in 2008 and also in 2010. He was the opening keynote speaker for the 9th International Conference on Visual Information Systems, the Editor-in-Chief of the International Journal of Multimedia Information Retrieval (Springer), the co-founder of influential conferences such as the International Conference on Image and Video Retrieval, and the IEEE Workshop on Human Computer Interaction. He was also a founding member of the international advisory committee for the TRECVID video retrieval evaluation project, chair of the steering committee for the ACM International Conference on Multimedia Retrieval and a member of the ACM SIGMM Executive Committee. In addition, his work on convolutional fusion networks in deep learning won the best paper award at the 23rd International Conference on Multimedia Modeling. His work is frequently cited in both scientific and popular news sources.

The Large-Scale Concept Ontology for Multimedia project was a series of workshops held from April 2004 to September 2006 for the purpose of defining a standard formal vocabulary for the annotation and retrieval of video.

ACM Multimedia (ACM-MM) is the Association for Computing Machinery (ACM)'s annual conference on multimedia, sponsored by the SIGMM special interest group on multimedia in the ACM. SIGMM specializes in the field of multimedia computing, from underlying technologies to applications, theory to practice, and servers to networks to devices.

<span class="mw-page-title-main">James Z. Wang</span> Chinese-American computer scientist

James Ze Wang is a Chinese-American computer scientist. He is a distinguished professor of the College of Information Sciences and Technology at Pennsylvania State University. He is also an affiliated professor of the Molecular, Cellular, and Integrative Biosciences Program; the Computational Science Graduate Minor; and the Social Data Analytics Graduate Program. He is co-director of the Intelligent Information Systems Laboratory. He was a visiting professor of the Robotics Institute at Carnegie Mellon University from 2007 to 2008. In 2011 and 2012, he served as a program manager in the Office of International Science and Engineering at the National Science Foundation. He is the second son of Chinese mathematician Wang Yuan.

<span class="mw-page-title-main">Anastasios Venetsanopoulos</span> Canadian engineer (1941–2014)

Anastasios (Tas) Venetsanopoulos was a professor of electrical and computer engineering at Toronto Metropolitan University in Toronto, Ontario and a professor emeritus with the Edward S. Rogers Department of Electrical and Computer Engineering at the University of Toronto. In October 2006, Venetsanopoulos joined what was then Ryerson University and served as the founding vice-president of research and innovation. His portfolio included oversight of the university's international activities, research ethics, Office of Research Services, and Office of Innovation and Commercialization. He retired from that position in 2010, but remained a distinguished advisor to the role. Tas Venetsanopoulos continued to actively supervise his research group at the University of Toronto, and was a highly sought-after consultant throughout his career.

Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 106, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.

Zhang Hongjiang is a Chinese computer scientist and executive. He served as CEO of Kingsoft, managing director of Microsoft Advanced Technology Center (ATC) and chief technology officer (CTO) of Microsoft China Research and Development Group (CRD). Hongjiang is currently Chairman of BAAI. In 2022, he was elected to the National Academy of Engineering for his technical contributions and leadership in the area of multimedia computing.

Ricky J. Sethi is an Assistant Professor of Computer Science at Fitchburg State University and the Director of Research for The Madsci Network. He was appointed as a National Science Foundation (NSF) Computing Innovation Fellow by the Computing Community Consortium and the Computing Research Association. He has contributed significantly in the fields of machine learning, computer vision, social computing, and science education/eLearning.

<span class="mw-page-title-main">Jitendra Malik</span> Indian-American academic (born 1960)

Jitendra Malik is an Indian-American academic who is the Arthur J. Chick Professor of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He is known for his research in computer vision.

Keith W. Ross is an American scholar of computer science whose research has focused on Markov decision processes, queuing theory, computer networks, peer-to-peer networks, Internet privacy, social networks, and deep reinforcement learning. He is the Dean of Engineering and Computer Science at NYU Shanghai and a computer science professor at the New York University Tandon School of Engineering.

<span class="mw-page-title-main">Yong Rui</span> CTO of Lenovo

Yong Rui is the chief technology officer and senior vice president of Lenovo Group. He is in charge of Lenovo's technical strategy, research and development directions, and Lenovo Research, one of Lenovo's most important innovation engines.

<span class="mw-page-title-main">Gang Hua</span> Chinese-American computer scientist (born 1979)

Gang Hua is a Chinese-American computer scientist who specializes in the field of computer vision and pattern recognition. He is an IEEE Fellow, IAPR Fellow and ACM Distinguished Scientist. He is a key contributor to Microsoft's Facial Recognition technologies.

<span class="mw-page-title-main">Bernd Girod</span> American computer scientist

Bernd Girod is a German-American engineer, the Robert L. and Audrey S. Hancock Professor of Electrical Engineering at Stanford University. Girod is a member of the National Academy of Engineering.

<span class="mw-page-title-main">Gregory D. Hager</span> American computer scientist

Gregory D. Hager is the Mandell Bellmore Professor of Computer Science and founding director of the Johns Hopkins Malone Center for Engineering in Healthcare at Johns Hopkins University.

Jiebo Luo is a Chinese-American computer scientist, the Albert Arendt Hopeman Professor of Engineering and Professor of Computer Science at the University of Rochester. He is interested in artificial intelligence, data science and computer vision.

Hsiao-Wuen Hon is a Taiwanese-US researcher in speech technology, and coauthor of the book Spoken Language Processing. He is Corporate Vice President of Microsoft and Chairman of Microsoft's Asia-Pacific R&D Group.

<span class="mw-page-title-main">Edward Y. Chang</span> American computer scientist

Edward Y. Chang is a computer scientist, academic, and author. He is an adjunct professor of Computer Science at Stanford University, and Visiting Chair Professor of Bioinformatics and Medical Engineering at Asia University, since 2019.

References

  1. 1 2 "2016 Most Influential Scholars in Multimedia". Archived from the original on 2017-08-19. Retrieved 2017-08-18.
  2. 1 2 ACM Recognizes 2017 Fellows for Making Transformative Contributions and Advancing Technology in the Digital Age, Association for Computing Machinery, December 11, 2017, archived from the original on 2019-06-24, retrieved 2017-11-13
  3. ↑ "Shih-Fu Chang" (PDF). Columbia University Fu Foundation School of Engineering and Applied Science. 2018-12-25. Archived (PDF) from the original on 2021-11-02. Retrieved 2022-10-06.
  4. ↑ "Shih-Fu Chang's Google Scholar Profile". Archived from the original on 2016-08-10. Retrieved 2017-08-22.
  5. ↑ "UvA awards honorary doctorates to computer scientist Chang and epigeneticist Feinberg". Archived from the original on 2017-09-13. Retrieved 2017-09-13.
  6. ↑ "IEEE Fellows 2004 | IEEE Communications Society".
  7. ↑ 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.
  8. ↑ Chang, Shih-Fu, William Chen, Horace J. Meng, Hari Sundaram, and Di Zhong. "A fully automated content-based video search engine supporting spatiotemporal queries." Circuits and Systems for Video Technology, IEEE Transactions on 8, no. 5 (1998): 602-615.
  9. ↑ Naphade, Milind, John R. Smith, Jelena Tesic, Shih-Fu Chang, Winston Hsu, Lyndon Kennedy, Alexander Hauptmann, and Jon Curtis. "Large-scale concept ontology for multimedia." IEEE multimedia 13, no. 3 (2006): 86-91.
  10. ↑ 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.
  11. ↑ 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.
  12. ↑ Li, Hongzhi, Joseph G. Ellis, Heng Ji, and Shih-Fu Chang. "Event specific multimodal pattern mining for knowledge base construction." In Proceedings of ACM on Multimedia Conference, pp. 821-830. ACM, 2016.
  13. ↑ Amir, Arnon, Marco Berg, Shih-Fu Chang, Winston Hsu, Giridharan Iyengar, Ching-Yung Lin, Milind Naphade et al. "IBM research TRECVID-2003 video retrieval system." NIST TRECVID-2003 (2003).
  14. ↑ 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.
  15. ↑ Pedro Szekely, et al., “Building and Using a Knowledge Graph to Combat Human Trafficking,” In International Conference on Semantic Web (ICSW), Oct. 2015.
  16. ↑ Columbia University Content-Based Image Search System for DARPA MEMEX Project. http://www.ee.columbia.edu/dvmm/memex/
  17. ↑ 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.
  18. 1 2 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.
  19. ↑ Wang, Jun, Eric Pohlmeyer, Barbara Hanna, Yu-Gang Jiang, Paul Sajda, and Shih-Fu Chang. "Brain state decoding for rapid image retrieval." In Proceedings of the 17th ACM international conference on Multimedia, pp. 945-954. ACM, 2009.
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