Fengli Xu is a data scientist, who uses data mining, machine learning, and network representation learning algorithms to investigate how citizens move and interact in urban space. His research interests span the fields of data science, urban science, and computational social science. He currently focuses on harnessing the power of newly available urban big data (e.g., street view images and mobile network records) and developing data-driven models for urban activities. Fengli was a Mansueto Institute Fellow and Postdoctoral Researcher at the University of Chicago Knowledge Lab. Fengli received his Ph.D. in Engineering from Tsinghua University in 2019, where he developed spatiotemporal data mining algorithms and stochastic models for urban mobility.