Seminar Details

SAT-Hub aims to provide better location-aware services to traveling public, especially for underserved populations including those with visual impairment, Autism Spectrum Disorder (ASD), or simply navigation challenges, with minimal infrastructure changes. The SAT-Hub project has the following three main technical components: (1). A SAT multilayer live facility model, with a building feature layer, a space information layer, a crowd dynamic layer, and a service information layer. (2). SAT hybrid mobile localization algorithms, using beacons, 2D/3D cameras and onboard sensors, integrated with the information from the multilayer model.  (3). SAT multimodal human-centered interfaces, with both the the layered model and the localization algorithms as the drivers for users with disabilities and/or travel challenges to better perform their traveling tasks. This talk will provide an overview of the project, with a number of sample results on various aspects of the cyber-physical-human ecosystem in research, development and commercialization. The research is a collaboration among CUNY, Rutgers, Lighthouse Guild and Bentley Systems, Inc., and is supported by the DHS Summer Research Team (SRT) Program, the NSF Smart and Connected Community Program, the NSF Partnerships of Innovation Program, and the Bentley Research Collaboration Program.

Bio:

Dr. Zhigang Zhu is currently Herbert G. Kayser Professor of Computer Science, at The City College and The Graduate Center, The City University of New York. He is Director of the City College Visual Computing Laboratory (CCVCL), and Co-Director of the Master’s Program in Data Science and Engineering at CCNY. Previously he was Associate Professor at Tsinghua University, Beijing and a Senior Research Fellow at the University of Massachusetts, Amherst. Dr. Zhu obtained his BS, MS and PhD degrees, all in Computer Science from Tsinghua University. His research interests include computer vision, multimodal sensing, human-computer interaction, and various applications in assistive technology, robotics, surveillance and transportation. Among other honors, he is a recipient of the President’s Award for Excellence at CCNY in 2013, and in 1999 his PhD thesis was selected into the Hundred National Excellent Doctoral Theses in China. He is an Associate Editor of Machine Vision Applications, Springer.