Shih-Fu Chang




Shih-Fu Chang’s research interest is focused on multimedia retrieval, computer vision, signal processing, and machine learning. He and his students have developed some of the earliest image/video search engines, such as VisualSEEk, VideoQ, and WebSEEk, contributing to the foundation of the vibrant field of content-based visual search and commercial systems for Web image search. Recognized by many best paper awards and high citation impacts, his scholarly work set trends in several important areas, such as compressed-domain video manipulation, video structure parsing, image authentication, large-scale indexing, and video content analysis. His group demonstrated the best performance in video annotation (2008) and multimedia event detection (2010) in the international video retrieval evaluation forum TRECVID.

The video concept classifier library, ontology, and annotated video corpora released by his group have been used by more than 100 groups. He co-led the ADVENT university-industry research consortium with the participation of more than 25 industry sponsors. He has received IEEE Signal Processing Society Technical Achievement Award, ACM SIGMM Technical Achievement Award, IEEE Kiyo Tomiyasu award, IBM Faculty award, and Service Recognition Awards from IEEE and ACM. He served as the general co-chair of ACM Multimedia conference in 2000 and 2010, Editor-in-Chief of the IEEE Signal Processing Magazine (2006-8), Chairman of Columbia Electrical Engineering Department (2007-2010), Senior Vice Dean of Columbia Engineering School (2012-date), and advisor for several companies and research institutes. His research has been broadly supported by government agencies as well as many industry sponsors. He is a Fellow of IEEE and the American Association for the Advancement of Science.

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E.g., 2016-10-21
E.g., 2016-10-21
E.g., 2016-10-21
May 15th 2016

Discover the relationship between Big Data and the Internet of Things (IoT). The Internet of Things is rapidly growing. It is predicted that more than 25 billion devices will be connected by 2020. In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors. You will also examine ways of analyzing event data, sentiment analysis, facial recognition software and how data generated from devices can be used to make decisions.

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