Kush R. Varshney
Mathematical Sciences and Analytics
IBM T. J. Watson Research Center
1101 Kitchawan Road
Yorktown Heights, NY 10598
(914)-945-1628


Tutorials, Talks, Posters, and Demonstrations

49. "Learning Classification Rules via Boolean Compressed Sensing with Application to Workforce Analytics," Optimization Seminar, Department of Operations Research and Financial Engineering, Princeton University, Princeton, New Jersey, January 22, 2014.

48. "Detecting Poverty with Satellite Imagery," Keynote Address, Big Data Summit, University of Illinois Research Park, Champaign, Illinois, November 5, 2014.

47. "Learning Classification Rules via Boolean Compressed Sensing with Application to Workforce Analytics," Communications Seminar, Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois, November 3, 2014.

46. "Detecting Poverty with Satellite Imagery," Data Analysts for Social Good Webinar, October 9, 2014.

45. "Learning Classification Rules via Boolean Compressed Sensing with Application to Workforce Analytics," Interdisciplinary Distinguished Seminar Series, Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, North Carolina, October 4, 2013.

44. "Proactive Retention among IBM Growth Market Employees," Using Analytics to Optimize Your Workforce Seminar, Analytics Solutions Center, Washington, District of Columbia, March 12, 2013.

43. "Business Analytics," IBM T. J. Watson Research Center, Cambridge, Massachusetts, November 7, 2012.

42. "SellerScope: Interactive Salesforce Analytics," IBM Information on Demand EXPO, Las Vegas, Nevada, October 21-24, 2012.

41. "SellerScope: Interactive Salesforce Analytics," IBM Investor Briefing, Yorktown Heights, New York, May 9, 2012.

40. "Introduction to Business Analytics," IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto, Japan, March 25, 2012.

39. "Classification of IT Service Tickets," IBM Worldwide Research Integrated Solutions Colloquium, Yorktown Heights, New York, January 25, 2012.

38. "SellerScope: Interactive, Prescriptive Salesforce Analytics," IBM Innovation Lab, Lotusphere, Orlando, Florida, January 15-19, 2012.

37. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," ╔cole Centrale, Paris, France, July 1, 2011.

36. "Supervised Classification in Sensor Networks," Communications, Networking, Signal and Image Processing Seminar, Purdue University, West Lafayette, Indiana, October 6, 2010.

35. "Supervised Classification in Sensor Networks," Business Analytics and Mathematical Sciences Department Seminar, IBM T. J. Watson Research Center, Yorktown Heights, New York, October 4, 2010.

34. "Frugal Hypothesis Testing and Classification," Applied Probability for Lunch, IBM T. J. Watson Research Center, Yorktown Heights, New York, May 19, 2010.

33. "Classification Using Geometric Level Sets," Machine Learning Tea, Cambridge, Massachusetts, February 15, 2010.

32. "Frugal Hypothesis Testing and Classification," Massachusetts Institute of Technology, Cambridge, Massachusetts, February 8, 2010.

31. "Distributed Dimensionality Reduction for Margin-Based Classification," LIDS Student Conference, Cambridge, Massachusetts, January 29, 2010.

30. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," General Electric Global Research Center, Niskayuna, New York, January 21, 2010.

29. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," MITRE Corporation, Bedford, Massachusetts, January 14, 2010.

28. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, December 10, 2009.

27. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," MIT Lincoln Laboratory, Lexington, Massachusetts, November 24, 2009.

26. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," IBM Thomas J. Watson Research Center, Yorktown Heights, New York, November 16, 2009.

25. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," Naval Research Laboratory, Washington, District of Columbia, November 10, 2009.

24. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," National Institute of Standards and Technology, Gaithersburg, Maryland, November 9, 2009.

23. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," School of Electrical and Computer Engineering, Cornell University, Ithaca, New York, November 6, 2009.

22. "Margin-Based Classification and Dimensionality Reduction Using Geometric Level Sets," Schlumberger-Doll Research Center, Cambridge, Massachusetts, November 2, 2009.

21. "Performance of Random Forests in the Low False Alarm and Low Missed Detection Regimes," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, October 14, 2009.

20. "Level Set Margin-Based Classification," Lawrence Livermore National Laboratory, Livermore, California, August 11, 2009.

19. "Random Forest Classifier Performance in Low False Alarm and Low Missed Detection Regimes," Lawrence Livermore National Laboratory Institutional Summer Student Poster Symposium, Livermore, California, August 6, 2009. (poster)

18. "Learning Dimensionality-Reduced Classifiers for Information Fusion," International Conference on Information Fusion, Seattle, Washington, July 9, 2009.

17. "The Epsilon Entropy of Level Set Classifiers," LIDS Student Conference, Cambridge, Massachusetts, January 30, 2009.

16. "Level Set Margin-Based Classification," MIT Lincoln Laboratory, Lexington, Massachusetts, January 16, 2009.

15. "Level Set Margin-Based Classification," Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, January 13, 2009.

14. "Supervised Learning of Classifiers via Level Set Segmentation," IEEE International Workshop on Machine Learning for Signal Processing, Canc˙n, Mexico, October 18, 2008.

13. "Classification and Linear Dimensionality Reduction via Level Set Segmentation," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, October 8, 2008.

12. "Minimum Mean Bayes Risk Error Quantization of Prior Probabilities," IEEE International Conference on Acoustics, Speech, and Signal Processing, Las Vegas, Nevada, April 1, 2008. (poster)

11. "Bayesian Hypothesis Testing with Prototype Priors," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, October 3, 2007.

10. "Multi-View Stereo Reconstruction of Total Knee Replacement from X-Rays," IEEE International Symposium on Biomedical Imaging, Arlington, Virginia, April 15, 2007. (poster)

9. "Discussion on Genomics," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, February 28, 2007.

8. "Wide-Angle SAR Image Formation with Sparsifying Regularization," MIT Lincoln Laboratory, Lexington, Massachusetts, January 30, 2007.

7. "From Different Angles," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, October 4, 2006.

6. "Wide-Angle SAR Image Formation with Sparsifying Regularization," Dipartimento di Ingegneria dellĺInformazione, FacoltÓ di Ingegneria, UniversitÓ di Pisa, Italy, July 17, 2006.

5. "Joint Image Formation and Anisotropy Characterization in Wide-Angle SAR," SPIE Defense and Security Symposium, Algorithms for Synthetic Aperture Radar Imagery XIII, Kissimmee, Florida, April 18, 2006. (poster)

4. "Wide-Angle SAR Imaging," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, April 5, 2006.

3. "A Sparse Signal Representation Framework for Anisotropy Characterization in SAR Imaging," LIDS Student Conference, Cambridge, Massachusetts, February 2, 2006.

2. "Anisotropy Characterization in Synthetic Aperture Radar using Sparse Signal Representation," Stochastic Systems Group, Massachusetts Institute of Technology, Cambridge, Massachusetts, October 5, 2005.

1. "Block-segmentation and Classification of Grayscale Postal Images," Bits on our Mind Symposium, Ithaca, New York, March 3, 2004.




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