Xiaofan Liang

Xiaofan Liang is an Assistant Professor of Urban and Regional Planning at Taubman College of Architecture & Urban Planning, University of Michigan – Ann Arbor. Liang is also affiliated with Michigan Institute for Data & AI in Society, UM Center for the Study of Complex Systems, and Science, Technology, and Public Policy Program. Liang is passionate about helping cities better understand and govern the complex networks and technologies that shape urban life. Liang’s research examines how network infrastructures such as mobility, social, and digital systems, as well as emerging AI technologies, shape, support, or hinder how cities function, how they are governed, and how residents experience everyday urban life.

Liang’s current work focuses on two themes: 1) Urban Networks, which investigates how infrastructure networks such as transportation, social, and digital infrastructure systems create tradeoffs between connectivity and place-based life, shape unequal experiences for different users and communities, and interact with other networks that compete for space, resources, and influence, 2) Urban AI, which explores how AI (and AI infrastructure) can support, transform, or challenge planning practices and public services.

Liang received her Master’s and PhD of City and Regional Planning from Georgia Institute of Technology, B.S. in Computational Science from Minerva University, and B.A. in Sociology from UC-Berkeley.