• Professor, Landscape Architecture & Urban Planning
  • Affiliated Faculty, Computer Science & Engineering
Google Scholar Profile
Xinyue Ye

Educational Background

  • Ph.D., Geographic Information Science, University of California at Santa Barbara - 2010

Research Interests

    • Geospatial artificial intelligence
    • Data science
    • Smart cities
    • Urban informatics

Awards & Honors

  • Fellow, American Association of Geographers (AAG)
  • Fellow, Royal Geographical Society
  • AAG Regional Development and Planning Distinguished Scholar Award in 2023
  • Inaugural Research Impact Award of Urban Planning (Texas A&M University) in 2023
  • Top 10 Young Scientists named by the World Geospatial Developers Conference in 2021
  • Outstanding Achievement in Research Award of Computing (New Jersey Institute of Technology) in 2019
  • Faculty Research Excellence Award of Geography (Kent State University) in 2014
  • Co-Editor of Annual Proceeding on IEEE International Conference on Geoinformatics since 2011

Selected Publications

  • Du, J., & Ye, X. (2023, November). Batch and negative sampling design for human mobility graph neural network training. In Proceedings of the 1st International Workshop on the Human Mobility Prediction Challenge (pp. 47-50).
  • Ye, X., Du, J., Han, Y., Newman, G., Retchless, D., Zou, L., Ham, Y., & Cai, Z. (2023). Developing human-centered urban digital twins for community infrastructure resilience: A research agenda. Journal of Planning Literature, 38(2), 187-199.
  • Ye, X., Du, J., Gong, X., Zhao, Y., AL-Dohuki, S., & Kamw, F. (2021). SparseTrajAnalytics: An interactive visual analytics system for sparse trajectory data. Journal of Geovisualization and Spatial Analysis, 5, 1-11. Ye, X., & Lin, H. (Eds.). (2020). Spatial synthesis: computational social science and humanities. Springer Nature.
  • Ma, C., Zhao, Y., AL‐Dohuki, S., Yang, J., Ye, X., Kamw, F., & Amiruzzaman, M. (2020, June). GTMapLens: Interactive lens for geo‐text data browsing on map. In Computer Graphics Forum (Vol. 39, No. 3, pp. 469-481).
  • Shamal, A. D., Kamw, F., Zhao, Y., Ye, X., Yang, J., & Jamonnak, S. (2019, October). An open source trajanalytics software for modeling, transformation and visualization of urban trajectory data. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC) (pp. 150-155). IEEE.
  • Shamal, A. D., Zhao, Y., Kamw, F., Yang, J., Ye, X., & Chen, W. (2019). QuteVis: Visually studying transportation patterns using multisketch query of joint traffic situations. IEEE computer graphics and applications, 41(2), 35-48.
  • Kamw, F., Al-Dohuki, S., Zhao, Y., Eynon, T., Sheets, D., Yang, J., Ye, X., & Chen, W. (2019). Urban structure accessibility modeling and visualization for joint spatiotemporal constraints. IEEE Transactions on Intelligent Transportation Systems, 21(1), 104-116.
  • Zhao, Y., Al-Dohuki, S., Eynon, T., Kamw, F., Sheets, D., Ma, C., Hu, Y., Ye, X., & Yang, J. (2016). Trajanalytics: a web-based visual analytics software of urban trajectory data. In Proceeding of IEEE Visualization Conference. Al-Dohuki, S., Wu, Y., Kamw, F., Yang, J., Li, X., Zhao, Y., Ye, X., Chen, W., Ma, C., & Wang, F. (2016).
  • Semantictraj: A new approach to interacting with massive taxi trajectories. IEEE transactions on visualization and computer graphics, 23(1), 11-20.
  • Huang, X., Zhao, Y., Ma, C., Yang, J., Ye, X., & Zhang, C. (2015). TrajGraph: A graph-based visual analytics approach to studying urban network centralities using taxi trajectory data. IEEE transactions on visualization and computer graphics, 22(1), 160-169.
Google Scholar Profile