Books/Patents/Awards

(includes Edited Conference Proceedings, Book Chapters, and Tutorials)

Books

  • C. Kamath, Scientific Data Mining: A Practical Perspective, SIAM, Philadelphia, May 2009 [more information]
  • R. L. Grossman, C. Kamath, P. Kegelmeyer, V. Kumar, and R. Namburu (Eds.), Data Mining for Scientific and Engineering Applications, Kluwer, October 2001. [more information]

Edited Conference Proceedings

  • Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath, and Srinivasan Parthasarathy, Proceedings of the 2014 SIAM International Conference on Data Mining (SDM), Philadelphia, Pennsylvania, April 2014.
  • Joydeep Ghosh, Zoran Obradovic, Jennifer Dy, Zhi-Hua Zhou, Chandrika Kamath, and Srinivasan Parthasarathy, Proceedings of the 2013 SIAM International Conference on Data Mining (SDM), Austin, Texas, May 2013.
  • Joydeep Ghosh, Huan Liu, Ian Davidson, Carlotta Domeniconi, and  Chandrika Kamath, Proceedings of the 2012 SIAM International Conference on Data Mining (SDM), Anaheim, California, April 2012.
  • Bing Liu, Huan Liu, Chris Clifton, Takashi Washio, and Chandrika Kamath, Proceedings of the 2011 SIAM International Conference on Data Mining (SDM). Phoenix, Arizona, April 2011.
  • Srinivasan Parthasarathy,  Bing Liu, Bart Goethals, Jian Pei, and Chandrika Kamath, Proceedings of the 2010 SIAM International Conference on Data Mining (SDM). Columbus, Ohio, April 2010.
  • H. Kargupta, J. Srivastava, C. Kamath, and A. Goodman (Eds.), Proceedings of the Fifth SIAM International Conference on Data Mining, Newport Beach, California, April 2005.
  • M. W. Berry, U. Dayal, C. Kamath, and D. Skillicorn (Eds.), Proceedings of the Fourth SIAM International Conference on Data Mining, Lake Buena Vista, Florida, April 2004.
  • D. Barbara and C. Kamath (Eds.), Proceedings of the Third SIAM International Conference on Data Mining, San Francisco, California, May 2003.

Patents

  • Erick Cantu-Paz and Chandrika Kamath, “Creating ensembles of oblique decision trees with evolutionary algorithms and sampling,” U.S. Patent No. 7,062,504 B2, June 13, 2006.
  • Chandrika Kamath and Erick Cantu-Paz, “Parallel object-oriented decision tree system,” U.S. Patent No. 7,007,035 B2, February 28, 2006.
  • Chandrika Kamath and Erick Cantu-Paz, “Creating Ensembles of Decision Trees through Sampling,” U.S. Patent No. 6,938,049 B2, August 30, 2005.
  • Chandrika Kamath, Chuck H. Baldwin, Imola K. Fodor, Nu A. Tang, “Parallel Object-Oriented, Denoising System Using Wavelet Multiresolution Analysis,” U.S. Patent 6,879,729 B2, April 12, 2005.
  • Chandrika Kamath, Erick Cantu-Paz, David Littau, “Using Histograms to Introduce Randomization in the Generation of Ensembles of Decision Trees,” U.S. Patent 6,859,804 B2, February 22, 2005.
  • Chandrika Kamath, Erick Cantu-Paz, “Parallel Object-Oriented Data Mining System,” U.S. Patent 6,675,164 B2, January 6, 2004.

Awards

Erick Cantu-Paz, Samson Cheung, Abel Gezahegne, Cyrus Harrison, Chandrika Kamath, and Nu Ai Tang, R&D 100 award for the “Sapphire scientific data mining software”, 2006. [For more information, see pp.10-11 in Science and Technology Review]


Book Chapters

  • C. Kamath, “Data Mining and Analysis”, invited contribution, Princeton Companion to Applied Mathematics, Princeton University Press, pp 350-360, September 2015.
  • C. Kamath, “Dimension reduction for streaming data,” book chapter in Data Intensive Computing: Architectures, Algorithms, and Applications, Ian Gorton and Deb Gracio, editors, Cambridge University Press, 2012, pp 124-156.
  • C. Kamath, N. Wale, G. Karypis, G. Pandey, V. Kumar, K. Rajan, N. F. Samatova, P. Breimyer, G. Kora, C. Pan, S.Yoginath, “Scientific Data Analysis”, book chapter in “Scientific Data Management: Challenges, Technology, and Deployment”, A. Shoshani and D. Rotem, editors, Chapman and Hall/CRC Press, pp 281-324, 2010.
  • Lazarevic, A., Kanapady, R., Kamath, C., Tamma K., Kumar, V., “Damage Detection Employing Novel Data Mining Techniques,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
  • Kamath, C., E. Cantu-Paz, S.-C. Cheung, I. K. Fodor, and N. Tang, “Experiences in mining data from computer simulations,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
  • Kamath, C., “Mining Science and Engineering Data: An Overview,” book chapter, Handbook of Data Mining, Nong Ye (ed.), pp 549-572, Lawrence Erlbaum Associates. New Jersey, 2003.
  • Cantu-Paz, E., and C. Kamath, “On the Use of Evolutionary Algorithms in Data Mining,” book chapter in Data Mining: A Heuristic Approach, Eds. H. Abbass, R. Sarker, and C. Newton, pp. 48-71, 2001.
  • C. Kamath, “On Mining Scientific Datasets,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, P. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 1-22, 2001.
  • Kamath, C, E., Cantu-Paz, I. K. Fodor, N. Tang, “Searching for Bent-Double Galaxies in the FIRST Survey,” book chapter in Data Mining for Scientific and Engineering Applications, eds. R. Grossman, C. Kamath, W. Kegelmeyer, V. Kumar, and R. Namburu, Kluwer, pp. 95-114, 2001.
  • Fodor, Imola, and Chandrika Kamath, “The Role of Multiresolution in Mining Massive Image Datasets,” in Multiscale and Multiresolution Methods, Lecture Notes in Computational Science and Engineering, T. J. Barth, T. Chan, and R. Haimes, (Eds.), Volume 20, Springer-Verlag, pp. 307-318, 2001.
  • Kargupta, Hillol, Chandrika Kamath, and Philip Chan, Distributed and Parallel Data Mining: Emergence, Growth, and Future Directions, epilogue in Advances in Distributed and Parallel Knowledge Discovery, AAAI Press/MIT Press, pages 409-417, 2000.
  • Kamath, Chandrika, and Ron Musick, “Scalable Data Mining through Fine-Grained parallelism: The Present and the Future,” in Advances in Distributed and Parallel Knowledge Discovery H. Kargupta and P. Chan, Eds., (AAAI Press/MIT Press), pages 29-77, 2000.

Tutorials

  • Kamath, C., “Mining Science and Engineering Data,” Tutorial at the Third SIAM International Conference on Data Mining, San Francisco, May 2003.
  • Kamath, C., “An introduction to Scientific Data Mining,” tutorial at the IPAM short program on Mathematical Challenges in Scientific Data Mining, UCLA, January 14-18, 2002.
  • R. Grossman, C. Kamath, V. Kumar, “Data mining for scientific and engineering applications,” Tutorial at Supercomputing 2001, November 2001.
  • Kamath, C., “Data Mining for Science and Engineering Applications,” Tutorial at the First SIAM Int. conference on Data Mining, Chicago, April 5-7, 2001.