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Xingquan (Hill) Zhu

I am an Associate Professor in the Dept. of Computer & Electrical Engineering and Computer Science , Florida Atlantic University . I received my Ph.D degree in Computer Science from Fudan University, Shanghai, China. I have been with a number of Research Institutions and Universities, including Microsoft Research Asia (Intern), Purdue University (West Lafayette, IN), University of Vermont (UVM: Burlington, VT), and University of Technology, Sydney (UTS: AU). My research mainly focuses on Data Mining, Machine Learning, Multimedia Systems, and Bioinformatics.

Address: Dept. of Computer & Electrical Engineering and Computer Science
                Engineering East (EE)-509, Florida Atlantic University
                777 Glades Road, Boca Raton, FL 33431, USA
Phone: +1-561-297-3452;    Email: xzhu3@fau.edu

Selected Publications [Complete List][DBLP][ Google] [ WISE-2015 Call for Workshop Proposals]

Journals

  1. Meng Fang, Jie Yin, and Xingquan Zhu, Active Exploration for Large Graphs, Data Mining and Knowledge Discovery, In-press.
  2. Shirui Pan, Jia Wu, and Xingquan Zhu, CogBoost: Boosting for Fast Cost-sensitive Graph Classification, IEEE Transactions on Knowledge and Data Engineering , In-press.
  3. Bin Li, Xingquan Zhu, Ruijiang Li, and Chengqi Zhang, Rating Knowledge Sharing in Cross-Domain Collaborative Filtering, IEEE Transactions on Cybernetics, 45(5):1054-1068, May 2015.
  4. Shirui Pan, Jia Wu, Xingquan Zhu, and Chengqi Zhang, Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification, IEEE Transactions on Cybernetics, 45(5):940-954, May 2015.
  5. Meng Fang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs, IEEE Transactions on Knowledge and Data Engineering , In-press.
  6. Jia Wu, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Boosting for Multi-Graph Classification, IEEE Transactions on Cybernetics, 45(3): 430-443, March 2015.
  7. Peng Zhang, Chuan Zhou, Peng Wang, Byron J. Gao, Xingquan Zhu, and Li Guo, E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams , IEEE Transactions on Knowledge and Data Engineering , 27(2): 461-474, February 2015.
  8. Jia Wu, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Bag Constrained Structure Pattern Mining for Multi-Graph Classification, IEEE Transactions on Knowledge and Data Engineering, 26(10):2382-2396, October, 2014.
  9. Yifan Fu, Bin Li, Xingquan Zhu, and Chengqi Zhang, Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach, IEEE Transactions on Knowledge and Data Engineering, 26(4):808-822, April, 2014.
  10. Xindong Wu, Xingquan Zhu, Gong-Qing Wu, and Wei Ding, Data Mining with Big Data, IEEE Transactions on Knowledge and Data Engineering, 26(1):97-107, January, 2014.
  11. Hanning Yuan, Meng Fang, and Xingquan Zhu, Hierarchical Sampling for Multi-Instance Ensemble Learning, IEEE Transactions on Knowledge and Data Engineering, 24(12):2900-2905, December 2013.
  12. Yifan Fu, Xingquan Zhu, and Ahmed Elmagarmid, Active Learning with Optimal Instance Subset Selection, IEEE Transactions on Cybernetics, 43(2):464-475, April, 2013.
  13. Xindong Wu, Kui Yu, Wei Ding, Hao Wang, and Xingquan Zhu, Online Feature Selection with Streaming Features, IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(5):1178-1192, May 2013.
  14. Xingquan Zhu, Cross Domain Semi-Supervised Learning Using Feature Formulation, IEEE Transactions on Systems Man and Cybernetics, Part B, 41(6):1727-1638, 2011.
  15. Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Stream Data Using Optimal Weight Classifier Ensemble, IEEE Transactions on Systems Man and Cybernetics, Part B, 40(6):1607-1621, December 2010.
  16. Xingquan Zhu and Ying Yang, A Lazy Bagging Approach to Classification, Pattern Recognition, 41(10): 2980-2992, October, 2008.
  17. Xindong Wu and Xingquan Zhu, Mining with Noise Knowledge: Error Awareness Data Mining, IEEE Transactions on Systems Man and Cybernetics, Part A, 38(4): 917-932, July, 2008.
  18. Xingquan Zhu and Xindong Wu, Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering, IEEE Transactions on Knowledge and Data Engineering, 18(10): 1435-1440, November, 2006.
  19. Xingquan Zhu, Xindong Wu, Ahmed Elmagarmid, Zhe Feng, and Lide Wu, Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective, IEEE Transactions on Knowledge and Data Engineering, 17(5): 665-677, May, 2005.
  20. Xingquan Zhu and Xindong Wu, Cost-Constrained Data Acquisition for Intelligent Data Preparation, IEEE Transactions on Knowledge and Data Engineering, 17(11): 1542-1556, November, 2005.
  21. Xingquan Zhu, Ahmed Elmagarmid, Xiangyang Xue, Lide Wu, and Ann Catlin, InsightVide: Towards Hierarchical Video Content Organization for Efficient Browsing, Summarization and Retrieval, IEEE Transactions on Multimedia, 7(4): 648-666, November, 2005.
  22. Xingquan Zhu and Xindong Wu, Class Noise vs. Attribute Noise: A Quantitative Study of Their Impacts, Artificial Intelligence Review, 22 (3-4):177-210, November 2004.
  23. Xingquan Zhu, Jianping Fan, Ahmed Elmagarmid, and Xindong Wu, Hierarchical Video Summarization and Content Description Joint Semantic and Visual Similarity, ACM / Springer Multimedia System Journal, 9(1):31-53, 2003.

Conference Proceedings

  1. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Chengqi Zhang, Multi-Graph-View Learning for Graph Classification, Proceedings of the IEEE 14th International Conference on Data Mining (ICDM '14), Shenzhen, China, December 14-17, 2014. (Best Paper Candidate)
  2. Fei Xie, Xindong Wu, and Xingquan Zhu, Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards, Proceedings of the IEEE 14th International Conference on Data Mining (ICDM '14), Shenzhen, China, December 14-17, 2014.
  3. Ting Guo, Xingquan Zhu, Jian Pei, and Chengqi Zhang, SNOC:Streaming Network Node Classification, Proceedings of the IEEE 14th International Conference on Data Mining (ICDM '14), Shenzhen, China, December 14-17, 2014.
  4. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, and Chengqi Zhang, Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning, Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management (CIKM '14) , Nov. 3-7, 2014, Shanghai, China.
  5. Lianhua Chi, Bin Li, and Xingquan Zhu, Context-Preserving Hashing for Fast Text Classification, Proceedings of the 2014 SIAM International Conference on Data Mining (SDM '14), April 24-26, 2014, Philadelphia, Pennsylvania, USA.
  6. Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Multi-Graph Learning with Positive and Unlabeled Bags, Proceedings of the 2014 SIAM International Conference on Data Mining (SDM '14), April 24-26, 2014, Philadelphia, Pennsylvania, USA.
  7. Lianhua Chi, Bin Li, and Xingquan Zhu, Fast Graph Stream Classification Using Discriminative Clique Hashing, Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD '13), April 14-17, 2013, Brisbane, Australia. (Best Paper Award)
  8. Jia Wu, Xingquan Zhu, Chengqi Zhang, and Zhihua Cai, Multi-Instance Multi-Graph Dual Embedding Learning, Proceedings of the 13th IEEE International Conference on Data Mining (ICDM '13), Dec. 7-10, 2013, Dallas, Texas, USA.
  9. Chun Zhou, Peng Zhang, Jing Guo, Xingquan Zhu and Li Guo, UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks, Proceedings of the 13th IEEE International Conference on Data Mining (ICDM '13), Dec. 7-10, 2013, Dallas, Texas, USA.
  10. Meng Fang, Jie Yin, and Xingquan Zhu, Transfer Learning across Networks for Collective Classification, Proceedings of the 13th IEEE International Conference on Data Mining (ICDM '13), Dec. 7-10, 2013, Dallas, Texas, USA.
  11. Meng Fang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, Active Class Discovery and Learning for Networked Data, Proceedings of the 13th SIAM International Conference on Data Mining (SDM '13), May 2-4, 2013, Austin, Texas, USA.
  12. Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Graph Stream Classification using Labelled and Unlabeled Graphs, Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE '13), April 8-11, 2013, Brisbane, Australia.
  13. Meng Fang, Xingquan Zhu, Bin Li, Wei Ding, and Xindong Wu, Self-Taught Active Learning from Crowds, Proceedings of the 12th IEEE International Conference on Data Mining (ICDM '12), December 10-13, 2012, Brussels, Belgium.
  14. Bin Li, Xingquan Zhu, Lianhua Chi, and Chengqi Zhang, Nested Subtree Hash Kernels for Large-scale Graph Classification over Streams, Proceedings of the 12th IEEE International Conference on Data Mining (ICDM '12), December 10-13, 2012, Brussels, Belgium.
  15. Meng Fang and Xingquan Zhu, I Don't Know the Label: Active Learning with Blind Knowledge, Proceedings of the 21st International Conference on Pattern Recognition (ICPR '12), November 11-15, 2012, Tsukuba, Japan. (Best Student Paper Award)
  16. Shirui Pan and Xingquan Zhu, CGStream: Continuous Correlated Graph Query for Data Streams, Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM '12), Oct. 29 - Nov. 2, 2012, Hawaii, USA.
  17. Guodong Song, Ling Chen, Xingquan Zhu, and Chengqi Zhang, TCSST: Transfer Classification of Short & Sparse Text Using External Data, Proceedings of the 21st ACM Conference on Information and Knowledge Management (CIKM '12), Oct. 29 - Nov. 2, 2012, Hawaii, USA.
  18. Dan He, Xingquan Zhu, and D. Stott Parker, How Does Research Evolve? Pattern Mining for Research Meme Cycles, Proceedings of the 11th IEEE International Conference on Data Mining (ICDM '11), Dec. 11-14, 2011, Vancouver, Canada.
  19. Peng Zhang, Byron J. Gao, Xingquan Zhu, and Li Guo, Enabling Fast Lazy Learning for Data Streams, Proceedings of the 11th IEEE International Conference on Data Mining (ICDM '11), Dec. 11-14, 2011, Vancouver, Canada.
  20. Peng Zhang, Jun Li, Peng Wang, Byron J. Gao, Xingquan Zhu, and J. Gao, Enabling Efficient Prediction for Ensemble Models on Data Streams, Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '11), San Diego, CA, USA, August 21-24, 2011.
  21. Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, and Xingquan Zhu, Tracking User-Preference Varying Speed in Collaborative Filtering, Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI '11), San Francisco, USA, August 7-11, 2011.
  22. Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, and Xindong Wu, Cross Domain Collaborative Filtering over Time, Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI '11), Barcelona, Spain, July 16-22, 2011.
  23. Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo, Classifier and Cluster Ensembling for Mining Concept Drifting Data Streams, Proceedings of the 10th IEEE International Conference on Data Mining (ICDM '10), Dec. 14-17, 2010, Sydney, Australia.
  24. Zhengyu Lu, Xindong Wu, Xingquan Zhu, and Josh Bongard, Ensemble Pruning via Individual Contribution Ordering, Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '10), July 25-28, 2010, Washington, DC, USA.
  25. Xingquan Zhu, Xindong Wu, and Chengqi Zhang, Vague One-Class Learning for Data Streams, Proceedings of the 9th IEEE International Conference on Data Mining (ICDM '09), December 6-9, 2009, Miami, FL, USA.
  26. Peng Zhang, Xingquan Zhu, and Li Guo, Mining Data Streams with Labeled and Unlabeled Training Examples, Proceedings of the 9th IEEE International Conference on Data Mining (ICDM '09), December 6-9, 2009, Miami, FL, USA.
  27. Xingquan Zhu and Ruoming Jin, Multiple Information Sources Cooperative Learning, Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI '09), July 11-17, 2009, Pasadena, California, USA.
  28. Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, and Yong Shi, Cleansing Noisy Data Streams, Proceedings of the 8th IEEE International Conference on Data Mining (ICDM '08), December, 2008, Pisa, Italy.
  29. Peng Zhang, Xingquan Zhu, and Yong Shi, Categorizing and Mining Concept Drifting Data Stream, Proceedings of the 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '08), August, 2008, Las Vegas, USA.
  30. Xingquan Zhu, Lazy Learning for Classifying Imbalanced Data, Proceedings of the 7th IEEE International Conference on Data Mining (ICDM '07), October 28-31, 2007, Omaha, USA.
  31. Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Data Streams, Proceedings of the 7th IEEE International Conference on Data Mining (ICDM '07), October 28-31, 2007, Omaha, USA.
  32. Xingquan Zhu and Xindong Wu, Discovering Relational Patterns across Multiple Databases, Proceedings of the 23rd IEEE International Conference on Data Engineering (ICDE '07), April 15-20, 2007, Istanbul, Turkey.
  33. Xingquan Zhu, Xindong Wu, Taghi Khoshgoftaar, and Yong Shi, An Empirical Study of the Noise Impact on Cost-Sensitive Learning, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI '07), January 6-12, 2007, Hyderabad, India.
  34. Xingquan Zhu and Xindong Wu, Mining Complex Patterns across Sequences with Gap Requirements, Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI '07), January 6-12, 2007, Hyderabad, India.

Selected Professional Services [Full List]

Associate Editors
  • IEEE Transactions on Knowledge and Data Engineering (TKDE) (2008-2012, 2014-Date)
  • International Journal of Social Network Analysis and Mining (SNAM) (2010-Date)
  • Journal of Big Data (JBD) (2013-Date)
  • Network Modeling Analysis in Health Informatics and Bioinformatics (NetMAHIB)(2014-Date)
  • International Journal of Monitoring & Surveillance Technologies Research (IJMSTR)(2014-Date)
  • Advances in Data Warehousing and Mining (ADWM) (2007-Date)
  • Knowledge and Information Systems Journal (KAIS) (2003-2008)
Conference Co-Chair
  • ICMLA-2012: The Eleventh IEEE International Conference on Machine Learning and Applications (ICMLA 2012), Boca Raton, USA, 2012
Program Committee Co-Chair
  • BIBE-2014: The 14th IEEE International Conference on BioInformatics and BioEngineering (BIBE-2014), Boca Raton, FL, USA, Nov. 10-12, 2014.
  • GRC-2013: The 2013 IEEE International Conference on Granular Computing (GRC-2013), Beijing, China, Dec. 13-15, 2013.
  • ICTAI-2011: The 23rd IEEE International Conference on Tools with Artificial Intelligence (ICTAI-2011), Boca Raton, FL, USA, Nov. 7-9, 2011.
  • ICMLA-2010: The Ninth IEEE International Conference on Machine Learning and Applications (ICMLA-2010), Washington DC, USA, Dec. 12-14, 2010.
Program Committee Vice-Chair (Senior PC)
  • ICTAI-2015: The 27th IEEE International Conference on Tools with Artificial Intelligence, Salerno, Italy, Nov. 9-11, 2015
  • ICDM-2013: The 13th IEEE International Conference on Data Mining, Dallas, Texas, USA, Dec. 8-11, 2013
  • CIKM-2013: The 22nd ACM International Conference on Information and Knowledge Management (KM Track), San Francisco, CA, USA. Oct. 27 - Nov. 1, 2013.
  • ICDM-2011: The 11th IEEE International Conference on Data Mining, Vancouver, Canada, Dec. 11-14, 2011.
  • CIKM-2011: The 20th ACM International Conference on Information and Knowledge Management (KM Track), Glasgow, Scotland, UK, Oct. 24-28, 2011.
  • ICMLA-2011: The 2011 IEEE International Conference on Machine Learning and Applications, Honolulu, Hawaii, USA, on December 18-21, 2011.
  • CIKM-2010: The 19th ACM International Conference on Information and Knowledge Management (KM Track), Toronto, Canada, Oct. 26-30, 2010.
Workshop Chair
  • WISE-2015: The 16th International Conference on Web Information Systems Engineering, Miami, FL USA, October 18-20, 2015.
  • ASONAM-2015: The 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Paris, France, August 25-28, 2015.
Tutorial Chair
  • ICDM-2013: The 13th IEEE International Conference on Data Mining (ICDM-2013), Dallas Texas, USA, Dec. 8-11, 2013.
  • ADMA-2012: The 8th International Conference on Advanced Data Mining and Applications (ADMA 2012), Dec. 15-18, Nanjing, China 2012.
Finance Chair
  • ICTAI-2011: The 23rd IEEE International Conference on Tools with Artificial Intelligence, Boca Raton, FL, USA, Nov. 7-9, 2011.
  • ICDM-2010: The 10th IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia, Dec. 14-17, 2010.
Student Travel Award Chair
  • KDD-2015: The 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 10-13, 2015.
Registration Chair
  • KDD-2012: The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Beijing, China, August 12-16, 2012.
Program Committee (over 180 times)
  • AI: The Australian Joint Conference on Artificial Intelligence (2012-2008)
  • ACML: Asian Conference on Machine Learning (2013-2009)
  • ASONAM: The International Conference on Advances in Social Networks Analysis and Mining (2013-2010)
  • CIKM: ACM International Conference on Information and Knowledge Management (2013-2010).
  • ECML/PKDD: The 2011 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (2011)
  • ICDM: The IEEE International Conference on Data Mining (2015-2009, 2007-2003)
  • KDD: The ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2015-2010, 2007)
  • PAKDD: The Pacific-Asia Conference on Knowledge Discovery and Data Mining (2015-2007)
  • SDM: The SIAM International Conference on Data Mining (2015-2012, 2009)
  • SEKE: The International Conference on Software Engineering and Knowledge Engineering (2015-2007)
  • WSDM: ACM International Conference on Web Search and Data Mining (2014, 2013)
  • WAIM: The International Conference on Web-Age Information management (2013, 2012, 2011, 2009)

Research Grants

  • Mining Multiple Information Sources through Collaborative and Comparative Analysis (Australian Research Council)
  • Database-centric data analysis of molecular simulations (NIH subcontract)
  • Comparative Pancreatic Cancer Study Using Discriminative Gene Regulatory Network (American Cancer Society ACS-IRG)
Teaching

Fall 2014
Course Offered/Offering at FAU Course Offered at UVM
Award and Membership

  • Australian Research Council (ARC) Future Fellowship (Level 2), 2010
  • Best Paper Award: The 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD '13), April 14-17, 2013, Gold Coast, Australia.
  • Best Student Paper Award: The 21st International Conference on Pattern Recognition (ICPR '12), November 11-15, 2012, Tsukuba, Japan.
  • Best Paper Award: The 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI '05), November 14-16, 2005. Hong Kong, China
  • IEEE Senior Member (2012-)

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