Publications by Year

J: Journal,     C: Conference,     W: Workshop,     B: Book/Book Chapter

    2023

  1. C Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang and Jun Luo. STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies. In SIAM International Conference on Data Mining (SDM'23) (Accepted).
  2. C Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou and Sergii Skakun. Auto-CAM: Label-Free Earth Observation Imagery Composition and Masking Using Spatio-Temporal Dynamics. AAAI Conference on Artificial Intelligence (AAAI'23). Washington D.C., 2023.
  3. C Guojun Wu, Xin Zhang, Ziming Zhang, Yanhua Li, Xun Zhou, Christopher Brinton, Zhenming Liu. Learning Lightweight Neural Networks via Channel-Split Recurrent Convolution. Winter Conference on Applications of Computer Vision (WACV'23), Waikoloa, Hawaii, Jan 3 - Jan 7, 2023.
  4. J Haoyi Xiong, Xun Zhou, David Bennett. Detecting Spatiotemporal Propagation Patterns of Traffic Congestion from Fine-grained Vehicle Trajectory Data. International Journal of Geographical Information Science (IJGIS), 2023 (Accepted).

    2022

  5. C Ronilo Ragodos, Tong Wang, Qihang Lin, and Xun Zhou. Explaining a Reinforcement Learning Agent via Prototyping. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS'22). (Acceptance rate = 25.6%).
  6. C Han Bao, Xun Zhou, Yiqun Xie, Yanhua Li and Xiaowei Jia, STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19. In Proc. IEEE International Conference on Data Mining (ICDM'22), Orlando, FL, Nov. 28- Dec. 1, 2022. (Full paper acceptance ratio = 9.77%)
  7. C Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, and Jun Luo, STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation. In Proc. IEEE International Conference on Data Mining (ICDM'22), Orlando, FL, Nov. 28- Dec. 1, 2022. (Full paper acceptance ratio = 9.77%)
  8. C Yingxue Zhang, Yanhua Li, Xun Zhou, and Jun Luo, Mest-GAN: Cross-City Urban Traffic Estimation with Meta Spatial-Temporal Generative Adversarial Networks. In Proc. IEEE International Conference on Data Mining (ICDM'22), Orlando, FL, Nov. 28- Dec. 1, 2022. (Full paper acceptance ratio = 9.77%)
  9. C Yichen Ding, Ziming Zhang, Xun Zhou, Yanhua Li. EgoSpeed-Net: Forecasting Speed-Control in Driver Behavior from Egocentric Video Data. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'22), Accepted. (Acceptance rate: 23.8%)
  10. C Erhu He, Yiqun Xie, Xiaowei Jia, Weiye Chen, Han Bao, Xun Zhou, Zhe Jiang, Rahul Ghosh and Praveen Ravirathinam. Sailing in the Location-Based Fairness-Bias Sphere. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'22), Accepted. (Acceptance rate: 23.8%)
  11. C Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh and Praveen Ravirathinam. Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract). The 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI'22), Sister Conference Best Paper Track. 2022
  12. C Bang An, Amin Vahedian, Xun Zhou, W. Nick Street and Yanhua Li. HintNet: Hierarchical Knowledge Transfer Networks for Traffic Accident Forecasting on Heterogeneous Spatio-Temporal Data. In SIAM International Conference on Data Mining (SDM'22), Alexandria, Virginia. (Acceptance ratio = 27.8%).
  13. J Yiqun Xie, Weiye Chen, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh and Praveen Ravirathinam. Harnessing Heterogeneity in Space with Statistically-Guided Meta-Learning. Knowledge and Information Systems (KAIS). Springer (Accepted).

    2021

  14. C Amin Vahedian and Xun Zhou. Precise Bayes Classifier: Summary of Results. In Proc. IEEE International Conference on Data Mining (ICDM'21), Auckland, New Zealand, Dec. 7-10, 2021. (Full paper acceptance ratio = 9.9%)
  15. C Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh and Praveen Ravirathinam. A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity. In Proc. IEEE International Conference on Data Mining (ICDM'21), Auckland, New Zealand, Dec. 7-10, 2021. (Full paper acceptance ratio = 9.9%) [ICDM'21 Best Paper Award!]
  16. C Xin Zhang, Yanhua Li, Xun Zhou, Oren Mangoubi, Ziming Zhang, Vincent Filardi, and Jun Luo, DAC-ML: Domain Adaptable Continuous Meta-Learning for Urban Dynamics Prediction. In Proc. IEEE International Conference on Data Mining (ICDM'21), Auckland, New Zealand, Dec. 7-10, 2021. (Full paper acceptance ratio = 9.9%)
  17. C Ziming Zhang, Guojun Wu, Yue Yue, Yanhua Li, and Xun Zhou. Deep Incremental RNN for Learning Sequential Data: A Lyapunov Stable Dynamical System. In Proc. IEEE International Conference on Data Mining (ICDM'21), Auckland, New Zealand, Dec. 7-10, 2021. (Full paper acceptance ratio = 9.9%)
  18. C Yingxue Zhang, Yanhua Li, Xun Zhou, Zhenming Liu, and Jun Luo. C3-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial Networks In Proc. IEEE International Conference on Data Mining (ICDM'21), Auckland, New Zealand, Dec. 7-10, 2021. (Short paper acceptance ratio = 20%)
  19. C Menghai Pan, Xin Zhang, Yanhua Li, Xun Zhou and Jun Luo. Learning Decision Making Strategies of Non-experts: A NEXT-GAIL Model for Taxi Drivers. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'21), 2021. (Accepted. Full paper acceptance rate: 22.4%).
  20. C Yiqun Xie, Xiaowei Jia, Han Bao, Xun Zhou, Jia Yu, Rahul Ghosh and Praveen Ravirathinam. Spatial-Net: A Self-Adaptive and Model-Agnostic Deep Learning Framework for Spatially Heterogeneous Datasets. In Proceedings of the ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'21), 2021. (Accepted. Full paper acceptance rate: 22.4%).
  21. J Han Bao, Xun Zhou, Yiqun Xie, Yingxue Zhang, Yanhua Li. COVID-GAN+: Estimating Human Mobility Responses to COVID-19 through Spatio-Temporal Generative Adversarial Networks with Enhanced Features. In ACM Transactions on Intelligent Systems and Technology (TIST), accepted.
  22. J Yiqun Xie, Xiaowei Jia, Shashi Shekhar, Han Bao and Xun Zhou. Significant DBSCAN+: Statistically Robust Density-based Clustering. In ACM Transactions on Intelligent Systems and Technology (TIST), accepted.
  23. J Yingxue Zhang, Yanhua Li, Xun Zhou, Jun Luo, and Zhi-Li Zhang. Urban Traffic Dynamics Prediction -- A Continuous Spatial-Temporal Meta-Learning Approach.. In ACM Transactions on Intelligent Systems and Technology (TIST), accepted.
  24. J Amin Vahedian Khezerlou, Xun Zhou, Xinyi Li, W. Nick Street, Yanhua Li. DILSA+: Predicting Urban Dispersal Events Through Deep Survival Analysis with Enhanced Urban Features. In ACM Transactions on Intelligent Systems and Technology (TIST), accepted.
  25. B Yanhua Li, Xun Zhou, Menghai Pan. Graph Neural Networks in Urban Intelligence. Chapter in "Graph Neural Networks: Foundations, Frontiers, and Applications" (Eds. L. Wu, P. Cui, J. Pei, and L. Zhao), Springer, pp 1--720, July 2021.

    26. 2020

  26. C Huimin Ren*, Menghai Pan*, Yanhua Li, Xun Zhou and Jun Luo. ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification. In Proc. the 26th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD'20), San Diego, CA, August 23 - 27, 2020, (acceptance ratio 16.8%=216/1279) (* co-first authors).
  27. C Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou and Jun Luo, xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis. In Proc. the 26th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD'20), San Diego, CA, August 23 - 27, 2020, (acceptance ratio 16.8%=216/1279).
  28. C Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong and Jun Luo. Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. In Proc. the 26th ACM SIGKDD conference on Knowledge Discovery and Data Mining (KDD'20), San Diego, CA, August 23 - 27, 2020, (Acceptance ratio 16.8%=216/1279).
  29. C Xin Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo. TrajGAIL: Trajectory Generative Adversarial Imitation Learning for Long-term Decision Analysis. 20th IEEE International Conference on Data Mining (ICDM'20) (accepted as long paper).
  30. C Yingxue Zhang, Yanhua Li, Xun Zhou and Jun Luo. cST-ML: Continuous Spatial-Temporal Meta-Learning for Traffic Dynamics Prediction. 20th IEEE International Conference on Data Mining (ICDM'20) (accepted as short paper).
  31. C Han Bao, Xun Zhou, Yingxue Zhang, Yanhua Li, and Yiqun Xie. COVID-GAN: Estimating Human Mobility Responses to COVID-19 Pandemic through Spatio-Temporal Conditional Generative Adversarial Networks. 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'20).(full paper, acceptance rate = 22.1%).
  32. C Yichen Ding, Xun Zhou, Han Bao, Yanhua Li, Cara Hamann, Steven Spears and Zhuoning Yuan. Cycling-Net: A Deep Learning Approach to Predicting Cyclist Behaviors from Geo-Referenced Egocentric Video Data. 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'20).(full paper, acceptance rate = 22.1%).
  33. C Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, Zhenming Liu, Jie Bao, Yu Zheng and Jun Luo. Is Reinforcement Learning the Choice of Human Learners? A Case Study of Taxi Drivers. 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'20).(full paper, acceptance rate = 22.1%).
  34. C Mingzhou Yang, Yanhua Li, Xun Zhou, Hui Lu, Zhihong Tian, Jun Luo. Inferring Passengers' Interactive Choices on Public Transits via MA-AL: Multi-Agent Apprenticeship Learning. In Proceedings of the Web Conference (WWW'20) (pp. 1637-1647). (acceptance ratio 19.2%=217/1129).
  35. J Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo. cGAIL: Conditional Generative Adversarial Imitation Learning—An Application in Taxi Drivers’ Strategy Learning. IEEE Transactions on Big Data (TBD) (accepted).
  36. J Yingxue Zhang, Yanhua Li, Xun Zhou Xiangnan Kong, Jun Luo. Off-Deployment Traffic Estimation --- A Traffic Generative Adversarial Networks Approach. IEEE Transactions on Big Data (TBD) (accepted).
  37. J Xiangyu Wang, Kang Zhao, Xun Zhou and W. Nick Street. Predicting User Posting Activities in Online Health Communities with Deep Learning. ACM Transactions on Management Information Systems (TMIS), 11 (3), 1-15.
  38. J Liang Wang, Xiaolong Xue and Xun Zhou. A New Approach for Measuring the Resilience of Transport Infrastructure Networks. Complexity (accepted).
  39. W Huigui Rong, Qun Zhang, Xun Zhou, Hongbo Jiang, Da Cao and Keqin Li. TESLA: A Centralized Taxi Dispatching Approach to Optimizing Revenue Efficiency with Global Fairness. The 9th ACM SIGKDD International Workshop on Urban Computing (Urbcomp'20) in conjuction with KDD'20.

    40. 2019

  40. C Amin Vahedian Khezerlou, Xun Zhou, Ling Tong, W. Nick Street, Yanhua Li. Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) (acceptance rate = 16%).
  41. C Xin Zhang, Yanhua Li, Xun Zhou, Jun Luo, Unveiling Taxi Drivers' Strategies via cGAIL - Conditional Generative Adversarial Imitation Learning. IEEE International Conference on Data Mining (ICDM'19), Beijing, China, Nov. 8-11, 2019.
  42. C Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo, TrafficGAN: Off-Deployment Traffic Estimation with Traffic Generative Adversarial Networks. IEEE International Conference on Data Mining (ICDM'19), Beijing, China, Nov. 8-11, 2019.
  43. C Menghai Pan, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Jun Luo. Dissecting the Learning Curve of Taxi Drivers: A Data-Driven Approach. In Proc. SIAM International Conference on Data Mining (SDM'19), 2019 (acceptance rate = 22.7%). (Best Applied Data Science Paper Award)
  44. J Amin Vahedian Khezerlou, Xun Zhou, Ling Tong, Yanhua Li, Jun Luo. Forecasting Gathering Events through Trajectory Destination Prediction: a Dynamic Hybrid Model. In IEEE Transactions on Knowledge and Data Engineering (TKDE). (In Press).
  45. J Yichen Ding, Xun Zhou, Guojun Wu, Yanhua Li, Jie Bao, Yu Zheng, Jun Luo. Mining Spatio-temporal Reachable Regions with Multiple Sources from Massive Trajectory Data. In IEEE Transactions on Knowledge and Data Engineering (TKDE). (In Press).
  46. J Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, Zhenming Liu, Rui Song, Hui Lu, Zhihong Tian, Jun Luo. DHPA: Dynamic Human Preference Analytics Framework - A Case Study on Taxi Drivers' Learning Curve Analysis. ACM Transactions on Intelligent Systems and Technology (TIST) 11.1 No.8, pp.1-19.
  47. J Yiqun Xie, Xun Zhou, Shashi Shekhar. Discovering Interesting Sub-paths with Statistical Significance from Spatio-Temporal Datasets. In ACM Transactions on Intelligent Systems and Technology (TIST) 11.1 No.2, pp.1-24.
  48. W Zhengcong Yin, Haoyi Xiong, Xun Zhou, Daniel W. Goldberg, Dave Bennett, Chong Zhang. A Deep Learning based Illegal Parking Detection Platform. In Proceedings of the 3rd ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI'19), pp. 32-35. 2019.
  49. W Yicheng Ding, Xun Zhou, Gautam Pant. Deep Learning with Interaction Terms: An Experimental Exploration. In 3rd INFORMS Workshop on Data Science, Seattle, WA, Oct. 19, 2019.
  50. W Amin Vahedian Khezerlou, Xinyi Li, Haoyi Xiong, Xun Zhou, Amy Colbert. Motivated or Exhausted: A Data-Driven Study of Taxi Driver Behavior Following Traffic Congestions. In 3rd INFORMS Workshop on Data Science, Seattle, WA, Oct. 19, 2019.
  51. B Michael R. Evans, Dev Oliver, KwangSoo Yang, Xun Zhou, Reem Y Ali, Shashi Shekhar. Enabling Spatial Big Data via CyberGIS: Challenges and Opportunities. In CyberGIS for Geospatial Discovery and Innovation (Ed. S. Wang and M. Goodchild), pp.143-170, Springer, Dordrecht, 2019

    2018

  52. C Zhuoning Yuan, Xun Zhou, Tianbao Yang. Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data. In Proc. 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'18), pp. 984-992, August 2018, London, UK. ACM.
  53. C Xiaoxuan Zhang, Mingrui Liu, Xun Zhou, Tianbao Yang. Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization. In Proc. Neural Information Processing Systems (NeurIPS'18), 2018.
  54. J Yichen Ding, Yanhua Li, Xun Zhou, Zhuojie Huang, Simin You, Jun Luo. Sampling Big Trajectory Data for Traversal Trajectory Aggregate Query. IEEE Transactions on Big Data (TBD). doi:10.1109/TBDATA.2018.2830780.
  55. J Xun Zhou, Huigui Rong, Chang Yang, Qun Zhang, Amin Vahedian Khezerlou, Hui Zheng, Zubair Shafiq, Alex X.Liu. Optimizing Taxi Driver Profit Efficiency: A Spatial Network-based Markov Decision Process Approach. IEEE Transactions on Big Data (TBD). DOI: 10.1109/TBDATA.2018.2875524
  56. J Tongxin Zhu, Tuo Shi, Jianzhong Li, Zhipeng Cai, Xun Zhou. Task Scheduling in Deadline-aware Mobile Edge Computing Systems. IEEE Internet of Things Journal 6, no. 3 (2018): 4854-4866.
  57. J Michael T. Lash, Min Zhang, Xun Zhou, Charles. F. Lynch, and W. Nick Street. Deriving Enhanced Geographical Representations via Similarity-based Spectral Analysis: Predicting Colorectal Cancer Survival Curves in Iowa. International Journal of Data Mining and Bioinformatics (IJDMB), accepted.
  58. W Haoyi Xiong, Amin Vahedian, Xun Zhou, Yanhua Li, Jun Luo. Predicting Traffic Congestion Propagation Patterns: A Propagation Graph Approach. In Proceedings of the 11th ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS), pp. 60-69. November 2018, Seattle, WA, USA. ACM. DOI:10.1145/3283207.3283213
  59. W Xiangyu Wang, Apoorva. Joshi, Xun Zhou, Kang Zhao. Social Support and User Churn Prediction for Online Health Communities - A Trajectory-based Deep Learning Method. In 28th Workshop on Information Technologies and Systems (WITS), Santa Clara, CA, USA, 2018.
  60. W Jeffrey Chiu, Amin Vahedian Khezerlou, and Xun Zhou. Understanding Business Location Choice Pattern: A Co-Location Analysis on Urban POI Data. In Proc. 2nd INFORMS Workshop on Data Science, Pheonix, AZ, 2018.

    61. 2017

  61. C Amin Vahedian Khezerlou, Xun Zhou, Ling Tong, Yanhua Li, Jun Luo. Forecasting Gathering Events through Continuous Destination Prediction on Big Trajectory Data. In Proceedings of 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'17) (full paper. Acceptance rate = 18%).
  62. C Michael T. Lash, Yuqi Sun, Xun Zhou, Charles F. Lynch and W. Nick. Street, Learning rich geographical representations: Predicting colorectal cancer survival in the state of Iowa. IEEE International Conference on Bioinformatics and Biomedicine (BIBM'17), Kansas City, MO, USA, 2017, pp. 778-785. doi:10.1109/BIBM.2017.8217754
  63. J Amin Vahedian Khezerlou, Xun Zhou, Lufan Li, Zubair Shafiq, Alex Liu, and Fan Zhang. A Traffic Flow Approach to Early Detection of Gathering Events: Comprehensive Results. In ACM Transactions on Intelligent Systems and Technology (TIST), 8(6) (2017): 74.
  64. J Dixian Zhu, Changjie Cai, Tianbao Yang, Xun Zhou. A Machine Learning Approach for Air Quality Prediction: Model Regularization and Optimization. In Big Data and Cognitive Computing, 2 (1) 5. DOI: 10.3390/bdcc2010005.
  65. W Zhuoning Yuan, Xun Zhou, Tianbao Yang, James Tamerius, Ricardo Mantilla. Predicting Traffic Accidents Through Heterogeneous Urban Data: A Case Study. In 6th ACM SIGKDD International Workshop on Urban Computing (UrbComp'17), Halifax, NS, Canada.
  66. W Liang Wang, Xiaolong Xue, Xun Zhou. Measuring the Resilience of Transportation Infrastructure Systems: A Case Study in China's Railway Network. In Proceedings of the MAIREINFRA International Conference on Maintenance and Rehabilitation of Constructed Infrastructure Facilities, Seoul, South Korea, July 19-21, 2017.
  67. B Shashi Shekhar, Hui Xiong, Xun Zhou (eds.), Encyclopedia of GIS, 2nd Edition. Springer. 2017.

    2016

  68. C Xun Zhou, Amin Vahedian Khezerlou, Alex Liu, Zubair Shafiq, Fan Zhang. A Traffic Flow Approach to Early Detection of Gathering Events. In 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'16).(Acceptance rate = 18%).
  69. C Huigui Rong*, Xun Zhou*, Chang Yang, Zubair Shafiq, Alex Liu. The Rich and the Poor: A Markov Decision Process Approach to Optimizing Taxi Driver Revenue Efficiency. In Proc. 25th ACM International Conference on Information and Knowledge Management (CIKM), pp. 2329-2334, Indianapolis, IN, Oct. 2016 (* co-first authors)(Acceptance rate (full + short) = 28.9%).
  70. J James D. Tamerius, Xun Zhou, Ricardo Mantilla, Tina Greenfield-Huitt. Precipitation Effects on Motor Vehicle Crashes Vary by Space, Time, and Environmental Conditions. Weather, Climate, and Society, 8(4), 399-407, 2016. DOI: 10.1175/WCAS-D-16-0009.1.
  71. B Xun Zhou, Shashi Shekhar, Reem Ali. Spatiotemporal Change Footprint Pattern Discovery. Chapter in S. Shekhar, H. Xiong & X. Zhou (eds.), Encyclopedia of GIS, 2nd Edition. Springer, 2016.

    72. 2015

  72. J Shashi Shekhar, Zhe Jiang, Reem Y. Ali, Emre Eftelioglu, Xun Tang, Venkata Gunturi, Xun Zhou. Spatiotemporal Data Mining: A Computational Perspective. ISPRS International Journal of Geo-Information, vol 4, 2015, 2306-2338.
  73. J Michael McDermotta, Sushil Prasad, Shashi Shekhar, Xun Zhou, Interesting Spatio-Temporal Region Discovery Computations Over Gpu and Mapreduce Platforms. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol 1, 2015, 35-41. (Best Paper Honorable Mention at 1st International Symposium on Spatio-temporal Computing).
  74. J Sushil K. Prasad, Michael McDermott, Satish Puri, Dhara Shah, Danial Aghajarian, Shashi Shekhar, Xun Zhou. A Vision for GPU-accelerated Parallel Computation on Geo-spatial Datasets. ACM SIGSPATIAL Special 6(3): 19-26.
  75. B Xun Zhou, Shashi Shekhar , Pradeep Mohan. Spatiotemporal change pattern mining: A multi-disciplinary perspective. In Mei-Po Kwan, Douglas Richardson, Donggen Wang, and Chenghu Zhou (eds.), Space-Time Integration in Geography and GIScience. pp. 301--326. Springer, Dordrecht.

    76. 2014

  76. C Emre Eftelioglu, Shashi Shekhar, Dev Oliver, Xun Zhou, Michael Evans, Yiqun Xie, James Kang, Renee Laubscher, and Christopher Farah. Ring-Shaped Hotspot Detection: A Summary of Results. In. Proc. 14th IEEE International Conference on Data Mining (ICDM'14), Shenzhen, China.
  77. C Dev Oliver, Shashi Shekhar, Xun Zhou, Emre Eftelioglu, Michael Evans, Qiaodi Zhuang, James Kang, Renee Laubscher and Christopher Farah. Significant Route Discovery: A Summary of Results. In Proc. the 8th International Conference on Geographic Information Science (GIScience'14), Vienna, Austria, September 2014.
  78. J Zhe Jiang, Shashi Shekhar, Xun Zhou, Joseph Knight, and Jennifer Corcoran. Focal-Test-Based Spatial Decision Tree Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27.6 (2014): 1547-1559.
  79. J Xun Zhou, Shashi Shekhar, Reem Y. Ali. "Spatiotemporal Change Footprint Pattern Discovery: an Inter-disciplinary Survey". WIREs Interdisciplinary Reviews: Data Mining and Knowledge Discovery (DMKD), Volume 4, Issue 1, pages 1-23, 2014.
  80. B Michael R. Evans, Dev Oliver, Xun Zhou, Shashi Shekhar. Spatial Big Data: Case Studies on Volume, Velocity, and Variety. In Hassan A. Karimi (ed.) Big Data: Techniques and Technologies in Geoinformatics. CRC. 2014.

    81. 2013

  81. C Zhe Jiang, Shashi Shekhar, Xun Zhou, Joseph Knight, and Jennifer Corcoran. "Focal-Test-Based Spatial Decision Tree Learning: A Summary of Results". In Proceedings of the 13th IEEE International Conference on Data Mining (ICDM'13). pp. 320-329.
  82. J Mohamed Sarwat, Mohamed F. Mokbel, Xun Zhou, Suman Nath: Generic and efficient framework for search trees on flash memory storage systems. GeoInformatica 17(3): 417-448 (2013)
  83. W Xun Zhou, Shashi Shekhar, Dev Oliver. "Discovering Persistent Change Windows in Spatiotemporal Datasets: A Summary of Results". In 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial'13), pp.37-46, Oralnado, FL, Nov. 2013. (Best paper award).
  84. W Sushil K Prasad, Shashi Shekhar, Michael McDermott, Xun Zhou, Michael Evans, Satish Puri: GPGPU-accelerated interesting interval discovery and other computations on GeoSpatial datasets: a summary of results. Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data (BigSpatial'13), pp.65-72, Oralnado, FL, Nov. 2013.
  85. W Sushil K. Prasad, Shashi Shekhar, Xi He, Satish Puri, Michael McDermott, Xun Zhou, Michael Evans. 2013. GPGPU-based data Structures and Algorithms for GeoSpatial Computation A Summary of Results and Future Roadmap. Position paper. Procs. The All Hands Meeting of the NSF CyberGIS project. Seattle, Sept. 2013.

    86. 2012 and before

  86. J Shashi Shekhar, KwangSoo Yang, Venkata M. V. Gunturi, Lydia Manikonda, Dev Oliver, Xun Zhou, Betsy George, Sangho Kim, Jeffrey M. R. Wolff, Qingsong Lu. Experiences with evacuation route planning algorithms. International Journal of Geographic Information Science (IJGIS) 26(12): 2253-2265 (2012)
  87. C Pradeep Mohan, Xun Zhou, Shashi Shekhar. Quantifying Resolution sensitivity of spatial autocorrelation: A Resolution Correlogram approach. In Proc. of 7th International Conference on Geographic Information Science (GIScience'12), Columbus, OH, USA, September 18-21, 2012.
  88. C Mohamed Sarwat, Mohamed F. Mokbel, Xun Zhou, Suman Nath. FAST: A Generic Framework for Flash-Aware Spatial Trees. In Proceedings of the 12th International Symposium on Spatial and Temporal Databases (SSTD'11), Minneapolis, MN, August 2011, pp. 149-167. (Best research paper award)
  89. C Xun Zhou, Shashi Shekhar, Pradeep Mohan, Stefan Liess and Peter K. Snyder. Discovering Interesting Sub-paths in Spatiotemporal Datasets: A Summary of Results. In Proc. 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL'11), Chicago, USA, Nov. 1-4, 2011, pp. 44-53. (Acceptance rate = 23%)
  90. J Xun Zhou, Betsy George, Sangho Kim, Jeffrey M. R. Wolff, Qingsong Lu, Shashi Shekhar, Evacuation Planning: A Spatial Network Database Approach. IEEE Data Engineering Bulletin 33(2): 26-31 (2010).
  91. J Xun Zhou, Jianzhong Li, Shengfei Shi. Distributed Aggregations for Two Queries over Uncertain Data. Journal of Computer Research and Development (in Chinese), 47 (5) 762-772 (2010). Won Best Student Paper Award at National Database Conference of China (NDBC'09).
  92. C Xun Zhou, Shengfei Shi, Jizhou Luo, and Wei Zhang. Lifetime Optimized Methods of Correlated Data Gathering on Sensor Networks. In Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD'07), vol. 2, pp. 3-8. IEEE, 2007.

    93. Technical Reports

  93. Xun Zhou, Shashi Shekhar, Reem Y. Ali. Spatiotemporal Change Footprint Pattern Discovery: An Interdisciplinary Survey. Technical Report (No. TR 14-023), Department of Computer Science and Engineering, University of Minnesota.
  94. Shashi Shekhar, Pradeep Mohan, Dev Oliver, Xun Zhou. Crime pattern analysis: A spatial frequent pattern mining approach. Technical Report (No. TR-12-015), Department of Computer Science and Engineering, University of Minnesota.