Personal website: http://www.terpconnect.umd.edu/~xie/

Yiqun Xie is an Assistant Professor of Geospatial Information Science at the University of Maryland, College Park. He received his PhD degree in Computer Science from the University of Minnesota, Twin Cities in 2020, advised by Dr. Shashi Shekhar. 

Dr. Xie's broad research area is on spatial data science and artificial intelligence (a.k.a. GeoAI). One size AI does not fit all. There are unique challenges (e.g., high cost of spurious patterns, spatial interdependency, spatial heterogeneity, limited training data/features) posed by spatial data and applications, limiting the use of traditional AI techniques. Dr. Xie's work investigates novel techniques and theoretical insights to bridge these gaps in applications such as smart cities, transportation, agriculture, Earth observation, etc.

Recognitions include best paper awards from leading spatial conferences in computer science*: Best Paper Award from SSTD'19 and Best Vision Paper Award from ACM SIGSPATIAL'19. His idea was also highlighted by the Great Innovative Ideas program at the Computing Community Consortium (part of the Computing Research Association). Earlier, he received the Best Poster Award (People's Choice) at the Symposium of University Consortium of Geographic Information Science in 2017.

Dr. Xie has served in the program committee of ACM SIGSPATIAL, and ACM SIGKDD Workshops on Urban Computing (UrbComp) and Fragile Earth (FEED). He also served as the Session Chair at the Spatial and Spatio-Temporal Data Mining (SSTDM) Workshop in IEEE ICDM 2018.

*In computer science, conferences are typically considered as important as journals based on both selectivity and impact.

Students who are interested in joining Dr. Xie's research team please email a resume to: xie [at] umd.edu