Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). His research interests focus on artificial intelligence (AI) and data science, with applications in smart cities in many contexts, including spatial-temporal data analytics, urban planning and optimization. Recently, his research has an emphasis on advancing imitation learning and meta learning in AI for learning and influencing the decision-making strategies of urban human agents, such as passenger-seeking strategies of taxi drivers and transit mode/route choices of urban travelers. Dr. Li received two Ph.D. degrees in computer science from University of Minnesota at Twin Cities in 2013, and in electrical engineering from Beijing University of Posts and Telecommunications, Beijing in China in 2009, respectively. His work has been honored with the Best Applied Data Science Paper Award at SDM 2019. His research has been funded by NSF CAREER and CRII Awards, and two projects with NSF Smart and Connected Communities (S&CC) Program.
Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). His research interests focus on artificial intelligence (AI) and data science, with applications in smart cities in many contexts, including spatial-temporal data analytics, urban planning and optimization. Recently, his research has an emphasis on advancing imitation learning and meta learning in AI for learning and influencing the decision-making strategies of urban human agents, such as passenger-seeking strategies of taxi drivers and transit mode/route choices of urban travelers. Dr. Li received two Ph.D. degrees in computer science from University of Minnesota at Twin Cities in 2013, and in electrical engineering from Beijing University of Posts and Telecommunications, Beijing in China in 2009, respectively. His work has been honored with the Best Applied Data Science Paper Award at SDM 2019. His research has been funded by NSF CAREER and CRII Awards, and two projects with NSF Smart and Connected Communities (S&CC) Program.
Scholarly Work
From Shortest-path to All-path: The Routing Continuum Theory and its applications 2014