profile

Yiqun Xie

Assistant Professor
Geospatial Information Science
University of Maryland, College Park

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

Email: xie at umd.edu

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. 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.

⧫ News

  • [Award] 2021/05: Received the NSF CISE CRII Award (PI; Program: CISE/IIS/III)!
  • [Award] 2021/05: Received the Dean's Research Initiative Award, University of Maryland!
  • [Paper] 2020/09: One paper accepted by International Journal of Geographical Information Science!
  • [Paper] 2020/08: Two full papers accepted by ACM SIGSPATIAL 2020!
  • [Best Paper] 2020/08: Received the Best Paper Award at the ACM SIGKDD'20 DeepSpatial Workshop!
  • [Paper] 2020/08: Two papers accepted by ACM Transactions on Data Science and DeepSpatial Workshop @ ACM SIGKDD!
  • [Paper] 2020/08: One paper accepted by Computers, Environment and Urban Systems!
  • [Thesis] 2020/06: Defended my PhD thesis (GeoAI: Challenges and Opportunities)!
  • [Highlight] 2020/01: Vision highlighted by Great Innovative Ideas of CCC @ Computing Resarch Association!
  • [Paper] 2020/01: Our paper has been accepted by ACM Transactions on Data Science (ACM TDS)!
  • [Best Paper] 2019/11: Received the Best Vision Paper Award at the ACM SIGSPATIAL 2019!
  • [Paper] 2019/08: Our paper has been accepted by the ACM SIGSPATIAL 2019!
  • [Best Paper] 2019/08: Received the Best Paper Award at SSTD 2019!
  • [Paper] 2019/06: Our paper has been accepted by ACM Transactions on Intelligent Systems and Technology (ACM TIST)!
  • [Paper] 2019/06: Our paper has been accepted by International Symposium on Spatial and Temporal Databases (SSTD'19)!
  • [Paper] 2019/05: Our paper has been accepted by International Journal of Geographical Information Science (IJGIS)!
  • [Paper] 2018/12: Our paper has been accepted by SIAM International Conference on Data Mining (SDM' 19)!
  • [Paper] 2018/08: Our paper has been accepted by IEEE International Conference on Data Mining (ICDM'18)!
  • [Paper] 2018/08: Our paper has been accepted by ACM SIGSPATIAL 2018!

⧫ Broad research areas

  • Data science and AI techniques to address unique challenges posted by spatial data/problems
    • Spatial autocorrelation and heterogeneity
    • High cost of spurious results
  • Technical topics:
    • Spatial-aware machine learning/deep learning
    • Statistically-robust clustering and pattern mining
    • Spatial optimization (e.g., eco-routing, allocation)
  • Application domains: Smart cities, agriculture, transportation, public health, public safety, etc.

⧫ Service

  • Program Committee, ACM SIGSPATIAL, 2021
  • Program Committee, ACM SIGKDD, 2021
  • Program Committee, ACM SIGKDD DeepSpatial Workshop, 2021
  • Program Committee, IJCAI, 2021
  • Program Committee, ACM SIGSPATIAL, 2020
  • Program Committee, ACM SIGSPATIAL Workshop on COVID, 2020.
  • Program Committee, ACM SIGKDD Workshop on Urban Computing (UrbComp), 2020.
  • Program Committee, ACM SIGKDD Workshop on Fragile Earth (FEED), 2020.
  • Session Chair, SSTDM (Spatial and Spatio-Temporal Data Mining) Workshop at IEEE ICDM 2018, Singapore.
  • Assisted with the writing of multiple proposals funded by NSF and USDA during PhD study.
  • Reviewer/external reviewer:
    • Journals (ACM Transactions on Intelligent Systems and Technology, ACM Transactions on Data Sciene, Remote Sensing of Environment, Geoinformatica, IJGIS, Trans. in GIS, ISPRS IJGI, Agriculture, Stat. in Med.)
    • Conferences (ACM SIGSPATIAL, SSTD, ACM SIGKDD, ICDM, IJCAI)
    • Workshops (COVID@SIGSPATIAL, FEED@SIGKDD, UrbComp@SIGKDD, DeepSpatial@SIGKDD)

⧫ Teaching

  • University of Maryland: Introduction to Spatial Artificial Intelligence
  • University of Minnesota (TA & Guest lectures): Machine learning, Spatial Data Science Research, Databases

⧫ Coverage

Great Innovative Ideas CCC Blog

⧫ Sponsors

Sincere gratitude to our sponsors from NSF and the University of Maryland.

nsf umd