Department of Computer Science faculty candidate Guang Wang will present a virtual lecture on Monday, March 14, at 3:30 p.m. via Zoom online meeting. In his talk, “Data-Driven Societal Cyber-Physical Systems for Smart Cities,” Wang will introduce his research on the foundations and applications of data-driven societal cyber-physical systems.
Talk Title: Data-Driven Societal Cyber-Physical Systems for Smart Cities
Abstract: In this talk, I will introduce my research on the foundations and applications of data-driven societal Cyber-Physical Systems (CPS), which technically integrates big data-driven modeling and socially informed decision-making to address real-world scientific and societal challenges in large-scale physical systems (e.g., mobility systems, smart payment systems, and on-demand delivery) with a human-centric design for Smart Cities. In particular, I will use mobility as a concrete scenario, and show how we address real-world challenges and advance human mobility by socially aware design. First, I will show how we conceptualize fairness to address the current large-scale electric vehicle charging problem efficiently and sustainably. Then, I will show how we utilize the data-driven societal CPS with a dynamic deadline design to support and enable accessible future shared autonomous mobility. Finally, I will discuss some future directions along the data-driven societal CPS research framework with focusing on different challenges for Smart Cities, e.g., privacy-preserving heterogeneous mobility data access, synthesis, and sharing, and explainable AI for the trustworthy gig economy, etc.
Bio: Guang Wang is a Postdoctoral Research Associate in the MIT Institute for Data, Systems, and Society (IDSS), Schwarzman College of Computing, working with Prof. Alex ‘Sandy’ Pentland as a member of the MIT Media Lab. He obtained his Ph.D. degree in Computer Science Under Prof. Desheng Zhang at Rutgers University. Guang is interested in the interplay between Cyber-Physical Systems, Big Data Analytics, Artificial Intelligence, and Human-Centered Computing. His research focuses on addressing real-world scientific and societal challenges with big data-driven modeling and socially informed decision-making, inspired by applications on Smart Cities and Human Mobility. He has been publishing extensively in top-tier Computer Science conferences and journals, including 35 papers in KDD, MobiCom, UbiComp, RTSS, ICDE, WWW, etc. He has been honored with the Outstanding Paper Award in the IEEE RTSS 2021. Visit Wang’s website here: http://guangwang.me/