Yiqun Xie

Assistant Professor
Geospatial Information Science
Affiliate Faculty
Artificial Intelligence Interdisciplinary Institute at Maryland (AIM)
University of Maryland, College Park

Ph.D in Computer Science
University of Minnesota, Twin Cities

Email: xie@umd.edu

CV: Xie_CV.pdf (10/02/2024)

Yiqun Xie is an Assistant Professor of Geospatial Information Science at the University of Maryland, College Park. He is faculty member of the Center for Geospatial Information Science and Department of Geographical Sciences, and an affiliate faculty member of the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM) at the University of Maryland. He received his PhD degree in Computer Science from the University of Minnesota, Twin Cities in 2020, advised by Dr. Shashi Shekhar. His broad research area is on spatial data science and artificial intelligence (a.k.a. Spatial-AI or GeoAI).

Students interested in joining Dr. Xie's team please send your resume to xie at umd dot edu. (Please feel free to follow up if you do not hear from me. It is likely you are on the waiting list for interview based on alignment with our research directions.)

⧫ News

• [College Award] 2025/04: Honored to receive the 2025 Early Career Impact Award!
• [Paper] 2025/03: One paper accepted by International Journal of Geographical Information Science!
• [Paper] 2024/12: One paper accepted by Communications of the ACM (IF: 22.7)!
• [Paper] 2024/12: One paper accepted by Remote Sensing of Environment (IF: 11.1)!
• [Paper] 2024/12: One paper accepted by SDM 2025!
• [Paper] 2024/12: One paper accepted by International Journal of Applied Earth Observation and Geoinformation!
• [Paper] 2024/12: Three papers accepted by AAAI 2025!
• [Organizer] 2024/12: Invited to join the Organizing Committee of ACM SIGSPATIAL as the Registration Chair!
• [Talk] 2024/12: Invited talk on AI for climate to current and emerging foreign leaders from U.S. Department of State's International Visitor Leadership Program!
• [Award] 2024/12: Our NASA AIST project has been selected for funding (PI)!
• [Affiliate] 2024/09: Invited to join the Artificial Intelligence Interdisciplinary Institute at Maryland (AIM) at UMD as an affiliate faculty member!
• [Paper] 2024/09: One paper accepted by NeurIPS 2024!
• [Award] 2024/08: Received the NSF Collaborations in AI and Geosciences (CAIG) Award (PI)!
• [Award] 2024/08: Received the NSF Civic Innovation Challenge Award, Planning Phase (Co-PI)!
• [Organizer] 2024/08: Invited to join the Organizing Committee of IEEE ICDM as the Local Chair!
• [Paper] 2024/08: One paper accepted by ACM SIGSPATIAL 2024!
• [Talk] 2024/08: Invited talk at the Knowledge-Guided Machine Learning (KGML) Workshop 2024!
• [Talk] 2024/07: Invited talk at the International Symposium on Spatiotemporal Data Science 2024!
• [Paper] 2024/05: One paper accepted by KDD 2024!
• [Research] 2024/03: Selected to be honored at the Maryland Research Excellence Celebration 2024!
• [Talk] 2024/03: Invited talk at the Value-Centered Artifitial Intelligence (VCAI)!
• [Paper] 2024/02: One paper accepted by IEEE Transactions on Knowledge and Data Engineering (TKDE)!
• [Organizer] 2024/12: Invited to join the Organizing Committee of IEEE Big Data as the Local Chair!
• [Paper] 2023/12: Three papers accepted by SDM 2024!
• [Paper] 2023/12: Four papers accepted at AAAI 2024!
• [Book Chapter] 2023/12: Chapter in "Handbook of Geospatial Artificial Intelligence" has been published online!
• [SIGSPATIAL SRC] 2023/11: Congratulations to undergraduate member Anh advancing to the finalist of the Student Research Competition at ACM SIGSPATIAL 2023!
• [Talk] 2023/10: Invited talk at the NSF iHARP institute (NSF HDR Institute for Harnessing Data and Model Revolution in the Polar Regions)!
• [Paper] 2023/09: Two papers accepted by ACM SIGSPATIAL 2023!
• [Paper] 2023/09: One paper accepted by ICDM 2023!
• [Book Chapter] 2023/08: Chapter in "Machine Learning for Data Science Handbook" has been published online!
• [Paper] 2023/08: One paper accepted by CIKM 2023!
• [Paper] 2023/07: One paper accepted by ICCV 2023!
• [Paper] 2023/06: One paper accepted by Knowledge and Information Systems (KAIS)!
• [NGAC Panel] 2023/05: Invited to join the AI Panel at the National Geospatial Advisory Committee's meeting!
• [Award] 2023/05: Received Google's AI for Social Good Award (PI; as gift)!
• [Best Paper] 2023/04: Received the Best Application Paper Award in SDM 2023!
• [Paper] 2023/04: Two papers accepted at IJCAI 2023!
• [NASEM Panel] 2023/03: Invited to talk at a GeoAI panel in the National Academies' GGSC Meeting (May 22)!
• [Award] 2023/02: Received Grand Challenges Grant (Team Project, Member), University of Maryland!
• [Paper] 2023/02: One paper accepted by Knowledge and Information Systems (KAIS)!
• [Award] 2023/01: Received Faculty-Student Research Award, University of Maryland!
• [Paper] 2022/12: Four papers accepted by SDM 2023!
• [Paper] 2022/11: Four papers accepted at AAAI 2023!
• [Paper] 2022/10: One paper accepted by Knowledge and Information Systems (KAIS)!
• [Paper] 2022/10: One paper accepted by IEEE BigData 2022!
• [SIGSPATIAL Cup] 2022/09: Solution selected as top-3 performances with an invited paper!
• [Keynote] 2022/09: To deliver a keynote talk at ACM SIGSPATIAL, ARIC Workshop on Nov. 1 in Seattle!
• [Paper] 2022/08: Two papers accepted by IEEE ICDM 2022 and ACM SIGSPATIAL 2022!
• [Award] 2022/05: Received the NSF/Amazon Fairness in AI (FAI) Award (UMD PI)!
• [Award] 2022/05: Received the NASA AIST Award (PI)!
• [Paper] 2022/05: One paper accepted by KDD 2022!
• [Best Presentation] 2022/03: Received the Best Presentation (Honorable Mention) at Google's AI for Social Good mid-program meeting!
• [Best Paper Track] 2022/02: Our paper is invited to the Sister Conference Best Paper Track at IJCAI 2022!
• [Paper] 2021/12: One paper accepted by AAAI 2022!
• [Paper] 2021/12: One paper accepted by SDM 2022!
• [Best Paper] 2021/11: Received the Best Paper Award at IEEE ICDM 2021! (link)
• [Paper] 2021/09: Our survey on statistically-robust clustering has been accepted by ACM Computing Surveys (CSUR)!

⧫ Broad research areas

• Spatial-aware machine learning/deep learning
• Physics-guided learning
• Statistically-robust clustering and pattern mining
• Spatial optimization (e.g., eco-routing, allocation)
• Related applications: Smart cities, agriculture, Earth science, transportation, public health, public safety, etc.

⧫ Coverage

⧫ Acknowledgements