Zhe Jiang Homepage

Books

  1. Zhe Jiang, Shashi Shekhar: Spatial Big Data Science - Classification Techniques for Earth Observation Imagery. Springer 2017, ISBN 978-3-319-60194-6, pp. 1-131

Journal Papers

  1. Zhe Jiang, Wenchong He, Marcus Stephen Kirby, Arpan Man Sainju, Shaowen Wang, Lawrence V. Stanislawski, Ethan J. Shavers, and E. Lynn Usery. "Weakly Supervised Spatial Deep Learning for Earth Image Segmentation Based on Imperfect Polyline Labels." ACM Transactions on Intelligent Systems and Technology (TIST) 13, No. 2 (2022): 1-20. (preprint pdf).
  2. Wenchong He, Arpan Man Sainju, Zhe Jiang, Da Yan, and Yang Zhou. "Earth Imagery Segmentation on Terrain Surface with Limited Training Labels: A Semi-supervised Approach based on Physics-Guided Graph Co-Training." ACM Transactions on Intelligent Systems and Technology (TIST) 13, No. 2 (2022): 1-22. (preprint pdf).
  3. Yang Zhou, Jiaxiang Ren, Ruoming Jin, Zijie Zhang, Jingyi Zheng, Zhe Jiang, Da Yan, and Dejing Dou. "Unsupervised Adversarial Network Alignment with Reinforcement Learning." ACM Transactions on Knowledge Discovery from Data (TKDD) 16, No. 3 (2021): 1-29. 28 pages, 2021.
  4. Zhihao Wei, Kebin Jia, Pengyu Liu, Xiaowei Jia, Yiqun Xie, and Zhe Jiang. "Large-scale river mapping using contrastive learning and multi-source satellite imagery." Remote Sensing 13, No. 15 (2021): 2893.
  5. Arpan Man Sainju, Wenchong He, Zhe Jiang, Da Yan, and Haiquan Chen. "Flood inundation mapping with limited observations based on physics-aware topography constraint." Frontiers in big Data 4 (2021).
  6. Lawrence V. Stanislawski, Ethan J. Shavers, Shaowen Wang, Zhe Jiang, E. Lynn Usery, Evan Moak, Alexander Duffy, and Joel Schott. "Extensibility of U-Net Neural Network Model for Hydrographic Feature Extraction and Implications for Hydrologic Modeling." Remote Sensing 13, No. 12 (2021): 2368.
  7. Zewei Xu, Shaowen Wang, Lawrence V. Stanislawski, Zhe Jiang, Nattapon Jaroenchai, Arpan Man Sainju, Ethan Shavers et al. "An attention U-Net model for detection of fine-scale hydrologic streamlines." Environmental Modelling & Software 140 (2021): 104992.
  8. Zhe Jiang, and Arpan Man Sainju. "A Hidden Markov Tree Model for Flood Extent Mapping in Heavily Vegetated Areas based on High Resolution Aerial Imagery and DEM: A Case Study on Hurricane Matthew Floods." International Journal of Remote Sensing 42, No. 3 (2021): 1160-1179.
  9. Zhe Jiang, Miao Xie, and Arpan Man Sainju. "Geographical Hidden Markov Tree." IEEE Transactions on Knowledge and Data Engineering (TKDE) 33, No. 2 (2021): 506-520. PDF
  10. Wenchong He, Zhe Jiang, “Semi-supervised Learning with the EM Algorithm: A Comparative Study between Unstructured and Structured Prediction”,IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 (accepted)
  11. Arpan Man Sainju, Wenchong He, Zhe Jiang, "A Hidden Markov Contour Tree Model for Spatial Structured Prediction", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020 (accepted)
  12. Zhe Jiang, "Spatial Structured Prediction Models: Applications, Challenges, and Techniques", IEEE Access, V8, 38714-38727, 2020 (Open Access)
  13. Arpan Man Sainju, Danial Aghajarian, Zhe Jiang, and Sushil Prasad. "Parallel Grid-Based Colocation Mining Algorithms on GPUs for Big Spatial Event Data." IEEE Transactions on Big Data (TBD) 6, No. 01 (2020): 107-118. PDF
  14. Arpan Man Sainju and Zhe Jiang, "Mapping Road Safety Features from Streetview Imagery: A Deep Learning Approach." ACM Transactions on Data Science 1, No. 3 (2020): 1-20. PDF
  15. Zhe Jiang, Arpan Man Sainju, Yan Li, Shashi Shekhar, and Joseph Knight. "Spatial ensemble learning for heterogeneous geographic data with class ambiguity." ACM Transactions on Intelligent Systems and Technology (TIST) 10, No. 4 (2019): 1-25. PDF
  16. Zhe Jiang. "A Survey on Spatial Prediction Methods." IEEE Transactions on Knowledge & Data Engineering (TKDE) 31, No. 09 (2019): 1645-1664. PDF
  17. Zhe Jiang, Michael Evans, Dev Oliver, and Shashi Shekhar. "Identifying K Primary Corridors from urban bicycle GPS trajectories on a road network." Information Systems 57 (2016): 142-159. PDF
  18. Anuj Karpatne, Zhe Jiang, Ranga Raju Vatsavai, Shashi Shekhar, and Vipin Kumar. "Monitoring land-cover changes: A machine-learning perspective." IEEE Geoscience and Remote Sensing Magazine (GRSM) 4, no. 2 (2016): 8-21.
  19. Emre Eftelioglu, Zhe Jiang, Reem Ali, and Shashi Shekhar. "Spatial computing perspective on food energy and water nexus." Journal of Environmental Studies and Sciences 6, no. 1 (2016): 62-76.
  20. 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, No. 6 (2015): 1547-1559.
  21. Shashi Shekhar, Zhe Jiang, Reem Ali, Emre Eftelioglu, Xun Tang, Viswanath Gunturi, Xun Zhou, "Spatiotemporal Data Mining: A Computational Perspective", Special Issue on Advances in Spatio-Temporal Data Analysis and Mining, ISPRS International Journal of Geo-Information, 4(4), 2306-2338, 2015 (link).

Conference Proceedings

  1. Wenchong He, Marcus Kirby, Zhe Jiang, Yiqun Xie, Xiaowei Jia, Da Yan, and Yang Zhou, ``Quantifying and Reducing Registration Uncertainty of Spatial Vector Labels on Earth Imagery", In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2022 (to appear)
  2. Guimu Guo, Da Yan, Lyuheng Yuan, Jalal Khalil, Cheng Long, Zhe Jiang, Yang Zhou, ``Maximal Directed Quasi-Clique Mining in a Large Graph", IEEE International Conference on Data Engineering (ICDE), 2022 (accepted)
  3. Da Yan, Md Mashiur Rahman Chowdhury, Guimu Guo, Zhe Jiang, Sushil K. Prasad, ``Distributed Task-Based Training of Tree Models", IEEE International Conference on Data Engineering (ICDE), 2022 (accepted)
  4. Xiaowei Jia, Shengyu Chen, Yiqun Xie, Haoyu Yang, Alison Appling, Samantha Oliver, Zhe Jiang, Modeling Reservoir Release in Stream Temperature Prediction Using Pseudo-Prospective Learning and Physical Simulations, SIAM International Conference on Data Mining (SDM), 2022
  5. Jiahao Ji, Jingyuan Wang, Zhe Jiang, Jiawei Jiang, "STDEN: Towards Physics-guided Neural Networks for Traffic Flow Prediction", (AAAI), 2022 (accepted)
  6. Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam, Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-Level Learning Framework, (AAAI) 2022 (accepted)
  7. Mirza Tanzim Sami, Da Yan, Huang Huang, Xinyu Liang, Guimu Guo, and Zhe Jiang. "Drone-Based Tower Survey by Multi-Task Learning." In 2021 IEEE International Conference on Big Data (Big Data), pp. 6011-6013. IEEE, 2021.
  8. Da Yan, Shengbin Wu, Mirza Tanzim Sami, Abdullateef Almudaifer, Zhe Jiang, Haiquan Chen, D. Rangaprakash, Gopikrishna Deshpande, and Yueen Ma. "Improving Brain Dysfunction Prediction by GAN: A Functional-Connectivity Generator Approach." In 2021 IEEE International Conference on Big Data (Big Data), pp. 1514-1522. IEEE, 2021.
  9. Zhe Jiang, Wenchong He, Marcus Kirby, Sultan Asiri, and Da Yan. "Weakly Supervised Spatial Deep Learning based on Imperfect Vector Labels with Registration Errors." In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), pp. 767-775. 2021.
  10. Xun Zhou, Liang Zhao, Zhe Jiang, Robert N Stewart, Shashi Shekhar, and Jieping Ye. "DeepSpatial'21: 2nd International Workshop on Deep Learning for Spatiotemporal Data, Applications, and Systems." In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), pp. 4183-4184. 2021.
  11. Zhang, Chengming, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Shuaiwen Song, and Dingwen Tao. "ClickTrain: efficient and accurate end-to-end deep learning training via fine-grained architecture-preserving pruning." In Proceedings of the ACM International Conference on Supercomputing (ICS), pp. 266-278. 2021.
  12. Wenchong He, Arpan Man Sainju, Zhe Jiang, and Da Yan. "Deep Neural Network for 3D Surface Segmentation based on Contour Tree Hierarchy." In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), pp. 253-261. Society for Industrial and Applied Mathematics, 2021.
  13. Guimu Guo, Da YAN, M. Tamer Özsu, Zhe Jiang, and Jalal Khalil. "Scalable mining of maximal quasi-cliques: an algorithm-system codesign approach." Proceedings of the VLDB Endowment (PVLDB) 14, no. 4 (2020): 573-585, ACM.
  14. Wenchong He, Zhe Jiang, Chengming Zhang, and Arpan Man Sainju. "Curvanet: Geometric deep learning based on directional curvature for 3d shape analysis." In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), pp. 2214-2224. 2020.
  15. Jiahao Ji, Jingyuan Wang, Zhe Jiang, Jingtian Ma, and Hu Zhang. "Interpretable Spatiotemporal Deep Learning Model for Traffic Flow Prediction based on Potential Energy Fields." In 2020 IEEE International Conference on Data Mining (ICDM), pp. 1076-1081. IEEE, 2020.
  16. Yuechun Gu, Da Yan, Sibo Yan, Zhe Jiang, "Price Forecast in High-Frequency Stock Market: An Autoregressive Recurrent Neural Network Model with Technical Indicators", ACM International Conference on Information and Knowledge Management (CIKM), 2020
  17. Yingzhe Dong, Da Yan, Abdullateef Ibrahim Almudaifer, Sibo Yan, Zhe Jiang, and Yang Zhou. "BELT: A Pipeline for Stock Price Prediction Using News." In 2020 IEEE International Conference on Big Data (Big Data), pp. 1137-1146. IEEE, 2020.
  18. Madhuri Ghorpade, Haiquan Chen, Yuhong Liu, and Zhe Jiang. "SMART: Emerging Activity Recognition with Limited Data for Multi-modal Wearable Sensing." In 2020 IEEE International Conference on Big Data (Big Data), pp. 1316-1321. IEEE, 2020.
  19. Arpan Man Sainju, Wenchong He, Zhe Jiang, and Da Yan. "Spatial classification with limited observations based on physics-aware structural constraint." In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Vol. 34, No. 01, pp. 898-905. 2020.
  20. Zhe Jiang, and Arpan Man Sainju. "Hidden markov contour tree: A spatial structured model for hydrological applications." In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), pp. 804-813. 2019. PDF, Source Codes
  21. Miao Xie, Zhe Jiang, and Arpan Man Sainju. "Geographical hidden markov tree for flood extent mapping." In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), pp. 2545-2554. 2018. PDF
  22. Aibek Musaev, Zhe Jiang, Steven Jones, Pezhman Sheinidashtegol, and Mirbek Dzhumaliev. "Detection of damage and failure events of road infrastructure using social media." In International Conference on Web Services, pp. 134-148. Springer, Cham, 2018.
  23. Zhe Jiang, Yan Li, Shashi Shekhar, Lian Rampi, and Joseph Knight. "Spatial ensemble learning for heterogeneous geographic data with class ambiguity: A summary of results." In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), pp. 1-10. 2017. PDF
  24. Benjamin Romano, and Zhe Jiang. "Visualizing traffic accident hotspots based on spatial-temporal network kernel density estimation." In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), pp. 1-4. 2017. PDF
  25. Arpan Man Sainju, and Zhe Jiang. "Grid-based colocation mining algorithms on gpu for big spatial event data: A summary of results." In International symposium on spatial and temporal databases (SSTD), pp. 263-280. Springer, Cham, 2017. PDF
  26. Sarnath Ramnath, Zhe Jiang, Hsuan-Heng Wu, Venkata MV Gunturi, and Shashi Shekhar. "A spatio-temporally opportunistic approach to best-start-time lagrangian shortest path." In International Symposium on Spatial and Temporal Databases (SSTD), pp. 274-291. Springer, Cham, 2015.
  27. Zhe Jiang, Shashi Shekhar, Xun Zhou, Joseph Knight, and Jennifer Corcoran. "Focal-test-based spatial decision tree learning: A summary of results." In IEEE 13th International Conference on Data Mining (ICDM), pp. 320-329. IEEE, 2013.
  28. Zhe Jiang, Shashi Shekhar, Pradeep Mohan, Joseph Knight, Jennifer Corcoran. "Learning spatial decision tree for geographical classification: a summary of results". In Proceedings of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), pp 390-393, 2012.
  29. Pradeep Mohan, Shashi Shekhar, James A. Shine, James P. Rogers, Zhe Jiang, Nicole Wayant. "A neighborhood graph based approach to regional co-location pattern discovery: a summary of results". In Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS), pp 122-132. 2011.

Workshop Papers

  1. Md Mostafijur Rahman, Arpan Man Sainju, Da Yan, and Zhe Jiang. "Mapping Road Safety Barriers Across Street View Image Sequences: A Hybrid Object Detection and Recurrent Model." In Proceedings of the 4th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, pp. 47-50. 2021.
  2. Arpan Man Sainju, Zhe Jiang, "Mapping Road Safety Features from Streetview Imagery: A Deep Learning Approach", ACM SIGKDD International Workshop on Urban Computing (UrbComp 2019), PDF

Book Chapters

  1. Arpan Man Sainju, Zhe Jiang, "Mining Colocation from Big Geo-spatial Event Data on GPU", Book Chapter in Handbook of Big Geospatial Data, Editors: Martin Werner, Yao-Yi Chiang. Springer. 2021.
  2. Xin zhao, Jeff Gray, Zhe Jiang, "Text Classification and Topic Modeling for Online Discussion Forums: An Empirical Study from the Systems Modeling Community”, Book chapter in Trends and Applications of Text Summarization Techniques, IGI Global, 2019
  3. Shashi Shekhar, Zhe Jiang, James Kang, Vijay Gandhi, "Spatial Data Mining", Book chapter in Encyclopedia of Database Systems, 2017.
  4. Shashi Shekhar, Yan Li, Reem Ali, Emre Eftelioglu, Xun Tang, Zhe Jiang, "Spatial and Spatiotemporal Data Mining", Book chapter in Comprehensive Geographic Information Systems, 264-286, Elsevier, 2017.
  5. Reem Y. Ali, Viswnath Gunturi, Zhe Jiang, Shashi Shekhar, "Emerging Applications of Spatial Net- work Big Data in Transportation." Book chapter in Big Data and Computational Intelligence in Networking. Taylor & Francis LLC, CRC Press, December 2017.
  6. Emre Eftelioglu, Zhe Jiang, Xun Tang, and Shashi Shekhar. "The Nexus of Food, Energy, and Water Resources: Visions and Challenges in Spatial Computing". Book Chapter In Advances in Geocomputation (pp. 5-20). Springer, Cham, 2017.
  7. Zhe Jiang, "Focal-Test-Based Spatial Decision Tree". Book chapter in Springer Encyclopedia of GIS: 622-627, 2017.