ACM SIGMM Award for Outstanding Technical Contributions to Multimedia Computing, Communications and Applications

The 2019 winner of the prestigious ACM Special Interest Group on Multimedia (SIGMM) award for Outstanding Technical Contributions to Multimedia Computing, Communications and Applications is Professor Mubarak Shah. The award is given in recognition of his outstanding and pioneering and continued research contributions in the areas of multimedia content analysis and multimedia applications, for leadership in education, and for outstanding and continued service to the multimedia community.
Mubarak Shah has made fundamental contributions which have had a tremendous impact in many important areas of multi-media content analysis and applications including video surveillance and monitoring, video retrieval, human action recognition,  object tracking, image tagging, visual crowd analysis, face recognition, shape-from-shading, and active contours.  With an h-index of more than 100 and more than 50,000 citation, Shah is among the top 100 Computer Science researchers and one of the most cited authors in computer vision in the world. He has single-handedly established a world-renowned Computer Vision research program at University of Central Florida (UCF), where one previously did not exist, which is currently ranked among the top ten in the US
In Multi-media content Analysis, Shah is most known for his pioneering work in Automated Video Surveillance, which has resulted in lots of follow up work, and mainly due to his initial work currently it is one of the most active areas of research. His team developed a series of novel methods for detecting and tracking humans and recognizing their behavior in surveillance videos. In a joint project funded by the Orlando Police Department, Shah’s group installed the first ever Automated Video Surveillance System, called Knight.  In 2015, the National Institute of Justice funded a two-year project that may revolutionize the way police monitor and analyze crime-scene surveillance video footage with technology developed at the University of Central Florida. “Utilizing the most advanced technology and tools to fight crime and keep our community safe is a top priority for the City of Orlando and this partnership will enhance these ongoing efforts,” said Orlando Police Chief John Mina. “The more eyes we have—whether they belong to officers or are created by technology—will further our mission to keep residents and visitors of Orlando safe and protected.”  
Shah’s research team has also developed a facial recognition tool: Who is my Daddy? That promises to be useful in rapidly matching pictures of children with their biological parents and in potentially identifying photos of missing children as they age. For example, Barbara Schudel sought Shah’s help in applying UCF's paternity recognition tool to confirm whether the man in her family photo was her father. After receiving the results of automated method from Dr. Shah’s graduate student, she replied in email: “Thank you from the bottom of my heart. You have made a 71-year old woman very happy”.
In addition, Professor Shah has made fundamental contributions to visual crowd analysis. He and his team developed original algorithms for accurately counting people in dense crowds, tracking an individual, and predicting crowd behavior to launch the world’s first automated crowd counting method. World's first automated crowd counting method was used for counting demonstrators calling for the independence of the Catalonia from Spain on September 11, 2015 and again in 2016.  In 2015, counting method was also licensed by Haj Core, Saudi Arabia for crowd management in Mecca. This breakthrough in Computer Vision can compute the size of crowds as large as hundreds of thousands in a less than a minute compared to the days and sometimes weeks of computer coupled with manual counting. It can also track and analyze hundreds of individuals at a time moving in dense crowds in order to predict dangerous pileups or spot suspicious behavior, saving many lives a year. 
As an educator, Shah has supervised 45 Ph.D. theses to completion. Besides mentoring doctoral students, Shah has mentored undergraduates and high school students.  He has served as a project director for the national site for Research Experience for Undergraduates (REU) in Computer Vision since 1987, funded by the US National Science Foundation (NSF) through a series of grants totalling $3 million. During the last 30 years, more than 300 undergraduates from 78 different institutions and 38 states have participated in this program.  In July 2017 during the Thirty Years Celebration of NSF REU at UCF, Dr. Shah was recognized by NSF and presented a plaque:  “For his outstanding and dedicated leadership and exemplary service in promoting quality undergraduate education, NSF commends Dr. Shah for establishing and maintaining an exemplary Research Experience for Undergraduates (REU) site for 30 years…”  His Computer Vision course on youtube has received more than million views.
Shah's theoretical work has attracted the attention of several companies including Lockheed Martin, SRI, Raytheon, Kitware, and Harris who have implemented and deployed his algorithms in the field. In appreciation of his work, Harris Corporation awarded him the Engineering Achievement Award in 1999. In 2005, Shah contributed to a large contract won by Lockheed under the US Army's FCS program. Shah's group was the only university group among 360 companies covering 150 congressional districts to receive a contract.
Shah is a Fellow of IEEE, AAAS, SPIE and IAPR.  In 2017, he was inducted to UCF Chapter of National Academy of Innovators (NAI). At UCF he has served as Assistant Vice President of Research and Interim Provost and Dean of College of Graduate Studies and he currently serves on Executive Committee of UCF Chapter of NAI. He holds seven US patents and have published Shah has published 6 books, 12 book chapters, more than 100 journal papers and more than 200  conference papers.
Shah’s service to the community is tremendous. He is an editor of international book series on Video Computing by Springer; was editor in chief of Machine Vision and Applications journal; an associate editor of ACM Computing Surveys journal (2002-2015), IEEE Transactions on PAMI; and guest editor of International Journal of Computer Vision, 2002.  He has also served as ACM and IEEE Distinguished Speaker
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