Chris Ding at University of Texas

Chris H.Q. Ding, Ph.D. Columbia University

Professor
Department of Computer Science and Engineering
University of Texas at Arlington

Office: Enginerring Research Building, Room 529
Mail: 500 UTA Blvd, Room 640
Arlington, TX 76019
Phone: 817-272-7041
FAX: 817-272-3784

Publications -- Citations --- Presentations -- Teaching -- Students -- Biography

Research Highlight (Data Mining / Machine Learning)

Principal Component Analysis provides relaxed solution to K-means clustering [2001] [2004]

Nonnegative matrix factorization is equivalent to K-means clustering [2005]

Tucker and ParaFac tensor decompositions perform simultaneous dimension reduction and K-means clustering [2008]

First error bounds for Tucker and ParaFac decompositions [2008]

Laplacian-based Min-Max Cut for Graph Partitioning and Data Clustering [2001] [Journal version]

Bipartite graph partitioning and data clustering (co-clustering) [2001]

Linearized cluster assignment via spectral ordering [2004].

Label propagation: Green's function for semi-supervised learning [2007].

Adaptive dimension reduction for clustering high dimensional data [2002] [2007]

Minimum redundancy maximum relevance (mRMR) feature selection [Paper codes data]

Research Highlights (Bioinformatics / Computational Biology)

Multi-class Protein Fold Recognition Using Support Vector Machines and Neural Networks (Paper , data).
A Unified Representation for Multi-Protein Complex Data for Modeling Protein Interaction Networks (PDF).
Comparative mapping of sequence-based and structure-based protein domains (paper online).
Minimum Redundancy - Maximum Relevance Feature Selection (PDF).

Tutorials

Bioinformatics and Bioimage Analysis (Link), November 2005
Principal Component Analysis and Matrix Factorizations for Learning (Link), August 2005
Spectral Clustering (Link), July 2004
Bioinformatics and Machine Learning Methods (Link), November 2003

Professional Activities

Conference /Workshop

ICDM 2010 Workshop on Optimization-based Methods for Emerging Data Mining Problems, Sydney, Australia, December 13, 2010
ICDM 2009 Workshop on Optimization-based Methods for Emerging Data Mining Problems, Miami Beach, December 5, 2009
KDD 2009 Workshop on Data Mining Using Matrices and Tensors (DMMT'09) , Paris, June 28, 2009.
KDD 2008 Workshop on Data Mining Using Matrices and Tensors (DMMT'09), Las Vegas, June 24, 2008.

Conference Commitees

Program Committee, Int'l Conf. on Knowledge Discovery and Data Mining (KDD'08),
Program Committee, IEEE Int'l Conf. on Data Mining (ICDM'08)
Program Committee, Computational Systems Bioinformactics Conference (CSB'07),
Program Committee, Int'l Conf. on Knowledge Discovery and Data Mining (KDD'07),
Program Committee, SIAM Int'l Conf. on Data Mining (SDM'07)
Program Committee, European Conf. on Machine Learning (ECML'06)
Senior Program Committee, Int'l Conf. on Knowledge Discovery and Data Mining (KDD'06),
Program Committee, Int'l Conf. on Machine Learning (ICML'06), Program Committee

Journals

Associate Editor, Int'l Journal of Data Mining and Bioinformatics
Guest Editor, DMKD Special Issue on Data Mining with Matrices, Graphs and Tensors, 2009.

Proposal Review / Panels

US National Science Foundation, 2004, 2005, 2006, 2007, 2008, 2009
US Department of Energy, 2008, 2009
National Science Foundation of Ireland, 2005.
Research Grants Council of Hong Kong, 2007.

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