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CSE department

SUNY Buffalo

Jing Gao University at Buffalo

Assistant Professor

Department of Computer Science and Engineering

University at Buffalo

350 Davis Hall, Buffalo, NY 14260

Phone: (716)645-1586

Email: jing@buffalo.edu


Brief Bio

I am currently an assistant professor in the Computer Science and Engineering Department of the University at Buffalo. I got my PhD from Computer Science Department at University of Illinois at Urbana Champaign in 2011 under the supervision of Prof. Jiawei Han. I received M.E. and B.E. from the Computer Science and Technology Department at Harbin Institute of Technology in China.

For Prospective Students

I am looking for motivated Ph.D. students who are interested in data mining and related areas. Please send me your CV and/or apply to CSE buffalo if you are interested. Graduate admission information can be found here.

Research Interests

I am broadly interested in data and information analysis with a focus on data mining and machine learning. In particular, I am interested in information integration, truth discovery, ensemble methods, crowdsourcing, data stream mining, transfer learning, anomaly detection and information network analysis. I am also interested in data management, information retrieval, social computing, text and web mining, statistical analysis, and data mining applications in health care, bioinformatics, transportation, education, and cyber security. [Research Overview]

Funded research project

Selected Recent Publications        Full List       Google Scholar

VLDB15

Qi Li, Yaliang Li, Jing Gao, Lu Su, Bo Zhao, Murat Demirbas, Wei Fan, Jiawei Han. A Confidence-Aware Approach for Truth Discovery on Long-Tail Data. International Conference on Very Large Data Bases, Kohala Coast, HI, August 2015, 8(4): 425-436.

KDD15

Yaliang Li, Qi Li, Jing Gao, Lu Su, Bo Zhao, Wei Fan, Jiawei Han. On the Discovery of Evolving Truth. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 675-684. Acceptance Rate: 159/819 = 19.4%. [Paper in PDF]

KDD15

Fenglong Ma, Yaliang Li, Qi Li, Minghui Qui, Jing Gao, Shi Zhi, Lu Su, Bo Zhao, Heng Ji, Jiawei Han. FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 675-684. Acceptance Rate: 159/819 = 19.4%. [Paper in PDF]

KDD15

Shi Zhi, Bo Zhao, Wenzhu Tong, Jing Gao, Dian Yu, Heng Ji, Jiawei Han. Modeling Truth Existence in Truth Discovery. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, Australia, August 2015, 675-684. Acceptance Rate: 159/819 = 19.4%. [Paper in PDF]

SIGMOD14

Qi Li, Yaliang Li, Jing Gao, Bo Zhao, Wei Fan, Jiawei Han. Resolving Conflicts in Heterogeneous Data by Truth Discovery and Source Reliability Estimation. ACM SIGMOD International Conference on Management of Data, Snowbird, UT, June 2014, to appear. [Paper in PDF] [Code&Data in ZIP] [More Informationn] [BIBTEX]

KDD13

Liang Ge, Jing Gao, Xiaoyi Li, Aidong Zhang. Multi-Source Deep Learning for Information Trustworthiness Estimation. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Chicago, IL, August 2013, 766-774. Acceptance Rate: 126/726 = 17.4%. [Paper in PDF] [BIBTEX]


Last updated: August 2015. Copyright (c) 2015 Jing Gao. All rights reserved.