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iXmatch: eXactly what you're looking for
iXmatch's scientists are world-renowned experts in the areas of advanced search, information retrieval, data fusion, text clustering and pattern discovery.

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Not that kind of scientists. iXmatch's computer scientists are internationally recognized experts in the areas of advanced search, information retrieval, data fusion, text clustering and pattern discovery. The have worked as Co-Principal Investigators at the U.S. Army High Performance Center at the University of Minnesota.

Dr. Eui-Hong (Sam) Han
Dr. Han received his Ph.D. in Computer Science from the University of Minnesota, where his research covered data mining, information retrieval, parallel algorithms, and artificial intelligence. He has published numerous research papers and received awards and honors for his work, including a Cray Research Fellowship. Prior to joining iXmatch, Dr. Han was a research associate at the University of Minnesota in the Army High Performance Computing Research Center, and worked for SGI/Cray Research and IBM. He has been a principal investigator on a research grant SBIR project for the Office of the Secretary of Defense (OSD) titled “Leadership Agent for Multi-source Information Fusion in Counter-Terrorism”. Dr. Han was the Tutorial Chair of the First SIAM International Conference on Data Mining in 2001 and a member of the organizing committee of the PAKDD workshop on Text Mining in 2002. He is a member of Phi Beta Kappa. For more information, visit his web site.

Dr. George Karypis
In addition to his role at iXmatch, Dr. Karypis is an assistant professor of computer science at the University of Minnesota. His research spans the areas of parallel algorithm design, data mining, bio-informatics, information retrieval, applications of parallel processing in scientific computing and optimization, sparse matrix computations, parallel preconditioners, and parallel programming languages and libraries. His research has resulted in the development of software libraries for serial and parallel graph partitioning, hypergraph partitioning, parallel Cholesky factorization, collaborative filtering-based recommendation algorithms, clustering high dimensional datasets, and finding frequent patterns in diverse datasets. He has coauthored over seventy journal and conference papers on these topics and two books on parallel computing. He is a member of ACM, IEEE, and SIAM. For details on his software work or publications, visit his web site.

Sai Chen
Ms. Chen received her MS in Computer Science from the University of Minnesota and her BE in Automation from the University of Science and Technology of China (USTC). Her research focused on classification and data mining. Prior to joining iXmatch, Ms. Chen developed image processing functions for Virtual Stepper® by Numerical Technologies Inc. (NASDAQ NMTC), which was awarded Editors’ Choice Best Product 2001 by Semiconductor International. As Principal Software Engineer for Spectra Electronic Systems Co. Ltd., Ms. Chen developed a pioneering credit card management system, POS (point-of-sale) systems for banks, and other financial and stock transaction systems.

Pacific-Asia Conference on Knowledge Discovery and Data Mining
Dr. Han and Dr. Karypis recently organized a workshop on text mining at The 6th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-02) in Taipei, Taiwan May 6th, 2002. The workshop brought together researchers from many disciplines and practices to present their current works and results in text mining. The program committee for the conference included other notable scientists, including:

  • Dr. Inderjit Dhillon, University of Texas at Austin
  • Dr. Susan Dumais, Microsoft
  • Dr. Matthias Kaiser, SAP
  • Dr. Boon-Toh Loh, Chinese University of Hong Kong
  • Dr. Jianchang Mao, Verity
  • Dr. Haesun Park, University of Minnesota
  • Dr. Prabhakar Raghavan, Head, Yahoo! Research
  • Dr. Andreas Rauber, Technische Universitat Wien, Austria
  • Dr. Zi-Jian Zheng, Blue Martini Software

    PAKDD-02 provided an international forum for the sharing of original research results and practical development experiences among researchers and application developers from around the world. In the workshop, Dr. Han led a discussion on how text mining provides knowledge discovery tools and approaches utilizing techniques from data mining, machine learning, information retrieval, natural-language understanding, statistics, database, and visualization.