May 8, 2019 –
Speaker: Suining He
Date: May 8
Location: HBL Video Theatre 2
Title: Ubiquitous Location-based Services for Smart Cities
With facilitating urbanization worldwide and exploding metropolitan population, building smart cities has attracted much attention recently due to its social and business significance. The resultant large volume of location data from ubiquitously-distributed mobile devices and transportation systems has provided unprecedented research opportunities as well as challenges. In this talk, I will discuss my works on the ubiquitous location-based services for smart cities, regarding the issues in sensor data noise, heterogeneous information sources, and spatial-temporal dynamics.
First, I present a novel smartphone location sensing technique called wireless fingerprint signal contour, mitigating influence of the sensor data noise. Second, I describe a joint optimization approach for bike sharing service providers to reconfigure their stations’ locations and dock sizes, fusing crowdsourced feedbacks and other information sources. Third, I introduce my research on balancing demands and supplies of ride-sharing services, by spatio-temporal reinforcement learning upon the urban mobility dynamics. I will conclude with thoughts on building data-driven models, algorithms, and information systems for smart cities and mobile computing research.
Dr. Suining He is currently working as a postdoctoral research fellow at the Real-Time Computing Lab (RTCL), Department of EECS, The University of Michigan, Ann Arbor. He received his Ph.D. degree at the Department of CSE, The Hong Kong University of Science and Technology (HKUST). His research interests include location-based services, mobile computing, data analytics and smart transportation. He is a Google PhD Fellow in Mobile Computing in 2015.