Rong Jin
Rong Jin
Associate Professor
Research Biography
Dr. Jin focuses his research on statistical machine learning and its application to information retrieval. He has worked on a variety of machine learning algorithms and their application to information retrieval, including retrieval models, collaborative filtering, cross lingual information retrieval, document clustering, and video/image retrieval. He has published over eighty conference and journal articles on related topics. Dr. Jin Ph.D. holds a Ph.D. in Computer Science from Carnegie Mellon University He received the NSF Career Award in 2006.
Research Interests
- information retrieval
Selected Publications
- R. Jin and J. Zhang, Multi-Class Learning by Smoothed Boosting, Journal of Machine Learning, 67(3): 207-227 (21), 2007
- R. Jin, L. Si, and C. X. Zhai, A Study of Mixture Models for Collaborative Filtering, Information Retrieval 9(3): 357-382, 2006
- Y. Li, R. Jin, and A. K. Jain, BoostCluster: Boosting Clustering by Pairwise Constraints. Proceedings Of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2007), pages 450-459, 2007
- S. Hoi, R. Jin, J. Zhu, and M. R. Lyu, Batch Mode Active Learning and Its Application to Medical Image Classification. Proceedings of the 21st International Conference on Machine Learning (ICML 2006), 417-424, 2006
Selected Achievements and Awards
- NSF Career Award, 2006