Nitesh V. Chawla

Assistant Professor

CONTACT INFORMATION

Computer Science and Engineering Department
353 Fitzpatrick Hall, Notre Dame
IN 46556
(574)631-8716
nchawla at cse dot nd.edu
  1. Upcoming Keynote Talk, NASA CIDU Conference, October 2009
  2. Learning from Imbalanced Datasets, Indiana University, Bloomington August 2009
  3. Learning to Knowledge Discovery to Action in Distribution Sensitive Scenarios, ASIAS Symposium, Washington DC, August 2009
  4. Learning to Knowledge Discovery to Action in Distribution Sensitive Scenarios, Oak Ridge National Labs, July 2009
  5. Modeling the product space as a network for causation and profitability, OCBC Bank Executive Talk, Singapore, April 2009
  6. Managing the Tipping Point: When, why and how a model may fail, SAS, Singapore, Apri 2009.
  7. Keynote talk, "A framework for monitoring classifiers performance: when and why failure occur" Quality issues, measures of interestingness and evaluation of data mining models Workshop at PAKDD April 2009.
  8. Personalized Disease Prediction from Electronic Health care databases, Indiana University School of Medicine, April 2009.
  9. "A recommendation system for disease prediction," University of Notre Dame Workshop on Biocomplexity, March 2009.
  10. "Prospective Health Care," Beth Israel Hospital, Harvard University, October 2008.
  11. "Following data: From learning to knowledge to action", University of Notre Dame, Center of Research Computing, November 2007.
  12. "The first line of action in health care prognostics," Center for Complex Networks Research, Northeastern University, 2007.
  13. "Learning in cost distribution sensitive environments," NIPS Workshop Series, December 2006.
  14. "Learning classifiers in unbalanced and cost-sensitive environments," University of Louisville, Kentucky, October 2006.
  15. "Data Mining in Customer Analytics and Beyond", Stern School, NYU, November 2005.
  16. "Biometrics Initiative at Notre Dame," National Institute of Justice, Washington DC, October 2005.
  17. "Taking Machine Learning to the Real World," Max Planck Institute of Biological Cybernetics, Germany, April 2005.
  18. "Biometrics: An overview", School of Informatics, Indiana University, April 2005.
  19. "Extreme learning: Learning from Massive, Imbalanced, and unlabeled data", GE Global Research, March 2004.
  20. "Data mining in Business Analytics: Mining for Insight and $$", Fair Isaac, CA, February 2004.
  21. "Extreme mining: Mining 'needles' in a hay-stack," IIT Mumbai, India, November 2003.
  22. "Learning on extremes --- size and imbalance --- of data", TATRC, US Army Medical Research and Material Command, Fort-Detrick, Maryland, May 2002.
  23. "Extreme Data Mining: What to do with a flood of training data?" INFORMS Conference, Miami, November 2001.
  24. "Learning to visualize large scientific data sets," Presentation to the local industry and federal government representatives. Intelligent Systems Open House, Department of Computer Science and Engineering, University of South Florida, April 26, 2000.