Professional Activities

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 ensemble methods, anomaly detection, semi-supervised learning, mining data streams and information networks. I am also interested in data management, information retrieval, social computing, text and web mining, statistical analysis, and data mining applications in cyber security, health care, bioinformatics, multimedia, energy and sustainability. [Research Overview]

Funded research project

Selected Recent Publications        Full List       Google Scholar


Sihong Xie, Jing Gao, Wei Fan, Deepak Turaga, Philip S. Yu. Class-Distribution Regularized Consensus Maximization for Alleviating Overfitting in Model Combination. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, August 2014, to appear. Acceptance Rate: 151/1036 = 14.6%. [Paper in PDF] [BIBTEX]


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]


Manish Gupta, Jing Gao, Charu Aggarwal, Jiawei Jan. Outlier Detection for Temporal Data. Morgan & Claypool, Synthesis Lectures on Data Mining and Knowledge Discovery, March 2014. [Link] [Amazon]


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]


Liang Ge, Jing Gao, Hung Q. Ngo, Kang Li, Aidong Zhang. On Handling Negative Transfer and Imbalanced Distributions in Multiple Source Transfer Learning. SIAM International Conference on Data Mining, Austin, TX, May 2013, 261-269. Acceptance Rate: 50/348 = 14.4%. Selected for publication in the special issue of "Best of SDM 2013" in Statistical Analysis and Data Mining [Conference version] [Journal version] [BIBTEX]

Last updated: June 2014. Copyright (c) 2014 Jing Gao. All rights reserved.