Hanhuai Shan

Ph.D. Candidate

Department of Computer Science and Engineering

University of Minnesota, Twin Cities

Address:   4-192  Kellor Hall (EE/CS Building),

                200 Union Street SE,

                Minneapolis, MN 55455

Phone:     612-625-0071

Email:      shan AT cs DOT umn DOT edu

Greetings! I am a Ph.D. candidate in Department of Computer Science and Engineering, University of Minnesota, Twin Cities.

My advisor is Prof. Arindam Banerjee. Before joining U of M, I received M.S. and B.S. from Department of Computer Science,

Zhejiang University in China.

Education

Sep. 2006 - now:              Ph.D. Candidate in Computer Science, University of Minnesota, Twin Cities.

Sep. 2004 - Jun. 2006:      M.S. in Computer Science, Zhejiang University, Hangzhou, China

Sep. 2000 - Jun. 2004:      B.S. in Computer Science, Zhejiang University, Hangzhou, China

Research Interests

Machine learning, Data mining, Graphical models, Bayesian inference, Clustering, Topic modeling, and Recommendation systems.

Working Experience

May. 2009 - Aug. 2009: Research Intern at NEC Laboratories America (Advisor: Dr. Guofei Jiang)

Teaching Experience

Sep. 2006 - Jan. 2007:  Teaching Assistant for Structure of Computer Programming

Publications

H. Wang, H. Shan and A. Banerjee.

Bayesian Cluster Ensembles.
Statistical Analysis and Data Mining, 2011.

[pdf]

H. Shan and A. Banerjee.

Generalized Probabilistic Matrix Factorizations for Collaborative Filtering.
IEEE International Conference on Data Mining (ICDM), Sydney, Australia, 2010.

(Acceptance rate: 19.45%) [pdf]

H. Shan and A. Banerjee.

Mixed-Membership Naive Bayes Models.
Data Mining and Knowledge Discovery (DMKD), 2010.

[pdf]

A. Agovic, H. Shan, and A. Banerjee.

Analyzing aviation safety reports: From topic modeling to scalable multi-label classification.
Conference on Intelligent Data Understanding (CIDU), Mountain View, U.S., 2010.

[pdf]

H. Shan, G. Jiang and K. Yoshihira.

Extracting Overlay Invariants of Distributed Systems for Autonomic System Management.

IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), Budapest, Hungary, 2010.

(Acceptance rate: 28.09%) [pdf]

H. Shan and A. Banerjee.

Residual Bayesian Co-clustering for Matrix Approximation.

SIAM International Conference on Data Mining (SDM), Columbus, U.S., 2010.

(Acceptance rate: 23.36%) [pdf]

H. Shan, A. Banerjee and Nikunj Oza.

Discriminative Mixed-membership Models.

IEEE International Conference on Data Mining (ICDM), Miami, U.S., 2009.

(Acceptance rate: 8.91%) [pdf]

H. Wang, H. Shan and A. Banerjee.

Bayesian Cluster Ensembles.

SIAM International Conference on Data Mining (SDM), Sparks, U.S., 2009.

(Acceptance rate: 15.67%) [pdf]

H. Shan and A. Banerjee.

Bayesian Co-clustering.

IEEE International Conference on Data Mining (ICDM), Pisa, Italy, 2008.

(Acceptance rate: 9.67%) [pdf]

H. Shan and A. Banerjee.

Anomaly Detection from ASRS Database of Textual Reports.

Conference on Intelligent Data Understanding (CIDU), Washington, D.C., U.S., 2008.

A. Banerjee and H. Shan.

Latent Dirichlet Conditional Naïve Bayes Models.

IEEE International Conference on Data Mining (ICDM), Omaha, U.S., 2007.

(Acceptance rate: 19.06%) [pdf]

Y. Zhuang, H. Shan and F. Wu.

An Approach for Cross-media Retrieval with Cross-reference Graph and PageRank.

International Multimedia Modeling Conference (MMM), Beijing, China, 2006.

[pdf]