Shih-Fu Chang

Shih-Fu Chang is the Richard Dicker Professor at Columbia University, with appointments in both Electrical Engineering Department and Computer Science Department. His 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. His 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.