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Jennifer Dy

334 Dana Research Center
360 Huntington Avenue
Boston, MA 02115


Dr. Jennifer G. Dy is an associate professor at the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, since 2002. She obtained her MS and PhD in 1997 and 2001 respectively from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, and her BS degree in 1993 from the Department of Electrical Engineering, University of the Philippines. She received an NSF Career award in 2004. She is an editorial board member for the journal, Machine Learning since 2004, publications chair for the International Conference on Machine Learning in 2004, and program committee member for ICML, ACM SIGKDD, AAAI, and SIAM SDM. Her research interests include Machine Learning, Data Mining, Statistical Pattern Recognition, and Computer Vision.


  • PhD, Purdue University, 2001. Joined Northeastern in 2002.

Research & Scholarship Interests

Machine learning; data mining; statistical pattern recognition; computer vision and image processing
Affiliated With

Department Research Areas

College Research Initiatives

Honors & Awards

  • NSF CAREER Award

Selected Publications

  • S.M. Brown, A. Webb, R.S. Mangoubi, J.G. Dy, A Sparse Combined Regression-classification Formulation for Learning a Physiological Alternative to Clinical Post-Traumatic Stress Disorder Scores, Twenty-ninth AAAI Conference on Artificial Intelligence, 2015
  • J. Ross, P. Castaldi, M. Cho, J.G. Dy, Dual Beta Process Priors for Latent Cluster Discovery in Chronic Obstructive Pulmonary Disease, ACM SIGKDD Knowledge Discovery and Data Mining, 2014
  • D. Niu, J.G. Dy, M.I. Jordan, Iterative Discovery of Multiple Alternative Clustering Views, IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(7), 2014, 1340-1353
  • Y. Yan, R. Rosales, G. Fung, J.G. Dy, Active Learning from Crowds, Proceedings of the 28th International Conference on Machine Learning (ICML), 2011, 1161-1168
  • Y. Guan, J.G. Dy, M.I. Jordan, A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection, Proceedings of the 28th International Conference on Machine Learning (ICML), 2011, 1073-1080
  • M. Masaeli, G. Fung, J.G. Dy, From Transformation-Based Dimensionality Reduction to Feature Selection, Proceedings of the 27th International Conference on Machine Learning (ICML), 2010, 751-758
  • Y. Yan, R. Rosales, G. Fung, M. Schmidt, J.G. Dy, et al., Modeling Annotator Expertise: Learning when Everybody Knows a Bit of Something, Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS), 9, 2010, 932-939
See Google Scholar Profile for all publications »

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March 31, 2016

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