Abstract
Rapidly developing mobile and sensor networks are accumulating massive volumes of human mobility data in cities. These data are by nature complex and involve multiple dimensions including space and time; in the real world, mobility behavior can vary given different internal (e.g., human, infrastructure attributes) and external factors (e.g., events). My research is motivated to take a data-driven approach in understanding the underlying dynamics and develop AI algorithms for modeling urban mobility, which plays a foundational role in the next-generation mobility services. This talk will also cover some tips for conducting interdisciplinary research, especially connecting AI and social science.
Biography
Zhaonan Wang joined NYU Shanghai in Fall 2024 as an Assistant Professor jointly appointed by Urban Studies and Computer Science. He obtained his PhD degree at the University of Tokyo in 2022, and did postdoctoral research in Spatial AI at University of Illinois Urbana-Champaign. Zhaonan’s research interests lie in an interdisciplinary area with an overarching goal to leverage AI to understand urban mobility and support decision making in the real-world scenarios. Zhaonan was awarded MEXT Scholar by Japanese Government in 2021; also, he was one of 37 nominees admitted to Peking University with College Entrance Exam exempted in Beijing 2010.