Xun Zhou

Profile image of Xun Zhou
Assistant Professor

Contact

Websites

Positions

  • Assistant Professor of Business Analytics

    Tippie College of Business

Education

  • PhD in Computer Science, University of Minnesota, 2014
  • MS in Computer Science, Harbin Institute of Technology, 2009
  • BS in Computer Science, Harbin Institute of Technology, 2007

Areas of Interest

  • Big Data Analytics
  • Machine Learning
  • Spatial and Spatio-Temporal Data Mining
  • Spatial Database
  • Sustainability
  • Urban Intelligence and Smart Cities

Professional Memberships

  • ACM SIGSPATIAL
  • Association for the Advancement of Artificial Intelligence
  • INFORMS

Selected Awards & Honors

  • Best Applied Data Science Paper Award, SIAM International Conference on Data Mining (SDM), 2019
  • Best Paper Honorable Mention, 1st International Symposium on Spatio-temporal Computing (ISSC)., 2015
  • NSF Student Travel Award, International Conference on Data Mining (ICDM), 2013
  • Best Paper Award, 2nd ACM SIGSPATIAL GIS Workshop on Big Geospatial Data Analytics (BigSpatial'13), 2013
  • Best Research Paper Award, 12th International Symposium on Spatial and Temporal Databases (SSTD), 2011
  • Best student paper award, China National Database Conference (NDBC), 2009

Selected Publications

  • Yang, M., Li, Y., Zhou, X., Lu, H., Tian, Z. & Luo, J. (In Press). Inferring Passengers’ Interactive Choices on Public Transits via MA-AL: Multi-Agent Apprenticeship Learning. The Web Conference (WWW).
  • Ding, Y., Zhou, X., Li, Y., Wu, G., Bao, J., Zheng, Y. & Luo, J. (In Press). Mining Spatio-temporal Reachable Regions with Multiple Sources from Massive Trajectory Data. IEEE Transactions on Knowledge and Data Engineering (TKDE).
  • Vahedian, A., Zhou, X., Tong, L., Li, Y. & Luo, J. (In Press). Forecasting Gathering Events through Trajectory Destination Prediction: A Dynamic Hybrid Model. IEEE Transactions on Knowledge and Data Engineering.
  • Zhang, Y., Li, Y., Zhou, X., Kong, X. & Luo, J. (In Press). Off-Deployment Traffic Estimation with Deep Conditional Generative Model. IEEE International Conference on Data Mining (ICDM 2019).
  • Zhang, X., Li, Y., Zhou, X. & Luo, J. (In Press). Unveiling Taxi Drivers’ Strategies via cGAIL - Conditional Generative Adversarial Imitation Learning. IEEE International Conference on Data Mining (ICDM 2019).
  • Pan, M., Li, Y., Zhou, X., Liu, Z., Song, R., Liu, H. & Luo, J. (2019). Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. Calgary: SIAM International Conference on Data Mining (SDM 2019).
  • Vahedian, A., Zhou, X., Tong, L., Street, N. & Li, Y. (2019). Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. Honolulu, Hawaii: The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-2019).
  • Yuan, Z., Zhou, X. & Yang, T. (2018). Hetero-ConvLSTM: A Deep Learning Approach to Traffic <br>Accident Prediction on Heterogeneous Spatio-Temporal Data. pp. 984-992. 24th ACM SIGKDD International Conference on Knowledge Discovery from Data (KDD'18). London, UK. ACM. DOI: 10.1145/3219819.3219922.
  • Khezerlou, A. V., Zhou, X., Li, L., Shafiq, Z., Liu, A. X. & Zhang, F. (2017). A Traffic Flow Approach to Early Detection of Gathering Events: Comprehensive Results. ACM Transactions on Intelligent Systems and Technology (TIST) 8 (6) 74.
  • Rong, H., Zhou, X., Yang, C., Shafiq, Z. & Liu, A. (2016). The Rich and the Poor: A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency. pp. 2329-2334. Indianapolis: 25th ACM International Conference on Information and Knowledge Management (CIKM 2016).
    • Expand publications

Selected Presentations

  • Yuan, Z. & Zhou, X. (2018, August) Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data. Poster presented at ACM SIGKDD International Conference on Knowledge Discovery from Data., London, United Kingdom.
  • Zhou, X. (2017, August) Predicting Traffic Accidents through Heterogeneous Urban Big Data: A Case Study. Conference Presentation presented at 6th ACM KDD International Workshop on Urban Computing.
  • Zhou, X. (2016, November) A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency. Conference Presentation presented at INFORMS Annual Meeting 2016, Nashville, Tennessee.
  • Zhou, X. & khezerlo, A. V. (2016, November) A Traffic Flow Approach to Early Detection of Gathering Events. Conference Presentation presented at ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), San Francisco, California.
  • Zhou, X. (2016, October) The Rich and the Poor: A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency. Poster presented at ACM International Conference on Information and Knowledge Management (CIKM), Indianapolis, Indiana.
  • Zhou, X. (2015, February) Spatiotemporal Big Data Analytics: Change Footprint Pattern Discovery. Oral presented at Kohn Colloquium, Iowa City, Iowa.
  • Zhou, X. (2014, November) Big Data Research and Graduate Study Overview. Lecture presented at First Year Seminar: Big Data, Cedar Rapids, Iowa.
  • Zhou, X. (2014, October) Spatiotemporal Big Data Analytics: Change Footprint Pattern Discovery. Oral presented at Departmental Colloquium, Iowa City.
  • Zhou, X. (2013, November) Discovering Persistent Change Windows in Spatiotemporal Datasets: A Summary of Results. Paper presented at ACM SIGSPATIAL Workshop on Big Geospatial Data Analytics (BigSpatial'13), Orlando, Florida.
  • Zhou, X. (2012, September) Quantifying Resolution Sensitivity of Spatial Autocorrelation: A Resolution Correlogram Approach. Paper presented at 7th International Conference on Geographic Information Sciences (GIScience), Columbus, Ohio.

Selected Grants & Contracts

  • Zhou, Xun (Investigator) Grant Deep Learning Methods for Traffic Accident Prediction. Sponsored by NVIDIA Corporation. Funded.
  • Zhou, Xun (Principal Investigator), Hamann, Cara (Co-Investigator), Spears, Steven (Co-Investigator) Grant Research, Basic. Understanding Bicyclists’ Behaviors Through Learning from Big Trip Data. Sponsored by SAFER-SIM University Transportation Center. Funded. July 1, 2019 - December 31, 2021.
  • Zhou, Xun (Principal Investigator) Grant CRII: III: Discovering Complex Change Footprint Patterns on Spatio-temporal Big Data for Urban Sustainability. Sponsored by National Science Foundation. Funded. July 1, 2016 - June 30, 2018.
  • Zhou, Xun (Principal Investigator), Shafiq, Zubair (Principal Investigator) Grant Heterogeneous Network Data Analytics to Improve Urban Sustainability. Sponsored by Obermann Center for Advanced Studies, University of Iowa. Funded. June 1, 2016 - June 30, 2016.

Professional Service

  • Program Committee Member, ACM International on Information and Knowledge Management (CIKM).
  • Program Committee Member, IEEE International Conference on Data Mining (ICDM).
  • Program Committee Member, AAAI International Conference on Artificial Intelligence.
  • Program Committee, ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Member, January 2020.
  • ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL)., Member, January 2019.
  • ACM SIGSPATIAL, Poster Co-Chair, ACM SIGSPATIAL International Conference on Advanced in Geographic Information Systems (GIS), January 2018.

Editorial & Review Activities

  • ACM Transactions on Intelligent Systems and Technology (TIST), Referee.
  • ACM Transactions on Knowledge Discovery from Data (TKDD), Referee.
  • Geoinformatica, Referee.
  • IEEE Transactions on Big Data, Reviewer.
  • IEEE Transactions on Knowledge and Data Engineering, Referee.
  • Information Systems Research, Referee.
  • MIS Quarterly, Referee.
  • Geoinformatica - Special Issue on Analytics for Local Events and News, Co-editor, January 2020.
  • ACM Transactions on Database Systems (TODS), Referee, January 2017.