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.
In particular, I
am interested in truth discovery, crowdsourcing, information integration, anomaly detection, information
network analysis, transfer learning, data stream mining, and ensemble learning. I am also interested in
various data mining applications in health care, bioinformatics, transportation, cyber security and education. [Research Overview]
Funded research project
Selected Recent Publications Full List Google Scholar
| KDD16 |
A Truth Discovery Approach with Theoretical Guarantee. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016, to appear. Acceptance Rate: 142/784 = 18.1%. [Paper in PDF] |
| KDD16 |
Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, August 2016, to appear. [Paper in PDF] |
| Survey |
A Survey on Truth Discovery. SIGKDD Explorations, 17(12): 1-16, December 2015. [Paper] |
| WSDM16 |
Crowdsourcing High Quality Labels with a Tight Budget. ACM International Conference on Web Search and Data Mining, San Francisco, CA, February 2016, 237-246. Acceptance Rate: 67/368 = 18.2%. [Paper in PDF] |
| SenSys15 |
Truth Discovery on Crowd Sensing of Correlated Entities. ACM International Conference on Embedded Networked Sensor Systems, Seoul, South Korea, November 2015, 169-182. Acceptance Rate: 27/132 = 20.5%. |
| VLDB15 |
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 |
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 |
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] |
| SDM15 |
Believe It Today or Tomorrow? Detecting Untrustworthy Information from Dynamic Multi-Source Data. SIAM International Conference on Data Mining, Vancouver, Canada, April 2015, 397-405. |
| SIGMOD14 |
Resolving Conflicts in Heterogeneous Data by Truth Discovery and Source Reliability Estimation. ACM SIGMOD International Conference on Management of Data, Snowbird, UT, June 2014, 1187-1198. [Paper in PDF] [Code&Data in ZIP] |