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.
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]
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]
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]
Referencesedit
^ ab"2016 Most Influential Scholars in Multimedia". from the original on 2017-08-19. Retrieved 2017-08-18.
^ abACM Recognizes 2017 Fellows for Making Transformative Contributions and Advancing Technology in the Digital Age, Association for Computing Machinery, December 11, 2017, from the original on 2019-06-24, retrieved 2017-11-13
^"Shih‐Fu Chang" (PDF). Columbia University Fu Foundation School of Engineering and Applied Science. 2018-12-25. (PDF) from the original on 2021-11-02. Retrieved 2022-10-06.
^"Shih-Fu Chang's Google Scholar Profile". from the original on 2016-08-10. Retrieved 2017-08-22.
^"UvA awards honorary doctorates to computer scientist Chang and epigeneticist Feinberg". from the original on 2017-09-13. Retrieved 2017-09-13.
^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.
^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.
^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.
^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.
^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.
^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.
^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).
^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.
^Pedro Szekely, et al., “Building and Using a Knowledge Graph to Combat Human Trafficking,” In International Conference on Semantic Web (ICSW), Oct. 2015.
^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.
^ abWu, 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, 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.
External linksedit
Shih-Fu Chang’s Home Page
Columbia Digital Video and Multimedia Lab
November 25, 2023
shih, chang, taiwanese, american, computer, scientist, electrical, engineer, noted, research, multimedia, information, retrieval, computer, vision, machine, learning, signal, processing, 张世富bornyunlin, taiwanalma, maternational, taiwan, university, university,. 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 Shih Fu Chang张世富BornYunlin TaiwanAlma materNational Taiwan University BS University of California Berkeley MS PhD AwardsNational Academy of Engineering 2023 National Academy of Inventors 2022 Academician Academia Sinica 2018 Fellow ACM Association for Computing Machinery 2017 Honorary Doctorate University of Amsterdam 2016 Technical Achievement Award IEEE Signal Processing Society 2012 Technical Achievement Award ACM Special Interest Group of Multimedia 2011 Fellow AAAS American Association for the Advancement of Science 2010 Fellow IEEE 2004 IEEE Kiyo Tomiyasu Award 2009 Scientific careerFieldsComputer science electrical engineeringInstitutionsColumbia UniversityWebsitewww wbr ee wbr columbia wbr edu wbr sfchangChang 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 Contents 1 Biography 2 Awards 3 Research 4 References 5 External linksBiography editChang 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 editChang s notable awards include Member National Academy of Engineering 2023 Member National Academy of Inventors 2022 Academician Academia Sinica 2018 Fellow ACM Association for Computing Machinery 2017 2 Most Influential Scholar in the Field of Multimedia 2016 1 Honorary Doctorate University of Amsterdam 384th Anniversary 2016 5 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 Fellow the American Association for the Advancement of Science 2010 IEEE Kiyo Tomiyasu Award 2009 Fellow the Institute of Electrical and Electronics Engineers 2004 for contributions to digital video and multimedia technologies 6 Research editChang 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 References edit a b 2016 Most Influential Scholars in Multimedia Archived from the original on 2017 08 19 Retrieved 2017 08 18 a b 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 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 Shih Fu Chang s Google Scholar Profile Archived from the original on 2016 08 10 Retrieved 2017 08 22 UvA awards honorary doctorates to computer scientist Chang and epigeneticist Feinberg Archived from the original on 2017 09 13 Retrieved 2017 09 13 IEEE Fellows 2004 IEEE Communications Society 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 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 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 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 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 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 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 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 Pedro Szekely et al Building and Using a Knowledge Graph to Combat Human Trafficking In International Conference on Semantic Web ICSW Oct 2015 Columbia University Content Based Image Search System for DARPA MEMEX Project http www ee columbia edu dvmm memex 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 a b 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 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 External links editShih Fu Chang s Home Page Columbia Digital Video and Multimedia Lab Retrieved from https en wikipedia org w index php title Shih Fu Chang amp oldid 1172373901, wikipedia, wiki, book, books, library,
