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EXPLORE NORTHEASTERN

Jennifer Dy

Professor,  Electrical and Computer Engineering

Contact

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Office

  • 515 ISEC
  • 617.373.3062

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Research Focus

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

About

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.

Education

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

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

Faculty

Sep 19, 2019

Ioannidis to Lead $1M NSF Grant for Real-Time Learning for Next Generation Wireless Systems

ECE Assistant Professor Stratis Ioannidis is leading a $1M NSF grant, with Professors Jennifer Dy, Tommaso Melodia, Associate Professor Kaushik Chowdhury, and Assistant Professor Yanzhi Wang, to develop “Efficient and Adaptive Real-Time Learning for Next Generation Wireless Systems”.

Faculty

Sep 17, 2018

$1.5M Wireless/Machine Learning DARPA Award for Device Fingerprinting

ECE Professor Kaushik Chowdhury is leading an interdisciplinary COE team leveraging a $1.5 million DARPA grant to identify device-specific radio signals on a massive scale.

Faculty

Aug 21, 2018

$1M NSF Grant to Understand Subjective Experiences

CCIS Assistant Professor Jan-Willem van de Meent (PI) and co-PIs ECE Professor Jennifer Dy, ECE Assistant Professor Sarah Ostadabbas, and COS Assistant Professor Ajay Satpute were awarded a $1M NSF grant “Leveraging Deep Probabilistic Models to Understand the Neural Bases of Subjective Experience”.

Faculty

Apr 28, 2017

Excellence in Research and Creative Activity Award

Congratulations to ECE professor Jennifer Dy for receiving the Excellence in Research and Creative Activity Award by the Office of the Provost. This award is presented to a full-time faculty member to honor outstanding research and creative activity of national and international significance. The president and the provost determine the recipients on the basis of […]

Graduate

Oct 27, 2016

ECE PhD student Wins ACM Student Research Competition

ECE PhD student Setareh Ariafar won First Place in the ACM Student Research Competition Graduate Level Finals at the Grace Hopper Celebration of Women in Computing Conference presenting her work on "Network-SVM: Support Vector Machine for Network Data".

Aug 18, 2016

$800K NSF Grant to Diagnose ROP

ECE Assistant Professor Stratis Ioannidis, Associate Professor Deniz Erdogmus, and Professor Jennifer Dy were awarded an $800K NSF grant to create an "Assistive Integrative Support Tool for Retinopathy of Prematurity".

May 02, 2016

Faculty and Staff Awards 2016

2016 Faculty and Staff Awards Congratulations to all the winners of the faculty and staff awards, and to everyone for their hard work and dedication during the 2015-2016 academic school year. Faculty Fellow Kaushik Chowdhury, ECE Carol Livermore, MIE Marilyn Minus, MIE Rising Star Staff Award Gabrielle Fiorenza, Co-op Nicole Nightingale, Dean’s Office Outstanding Teachers […]

Apr 21, 2016

I.Q. Project Highlight: Predicting Climate Change

How will marine organisms adapt and survive under extreme climate stressors, specifically, rising ocean temperatures and their extremes? This is an important question motiving ECE Professor Jennifer Dy and her research that would see the integration of statistics (with Prof. Adam Ding), computation, climate science (with Prof. Auroop Ganguly), and marine ecology (with Prof. Tarik […]

Mar 31, 2016

Professor Jennifer Dy Featured by Women in Machine Learning Group

ECE Professor Jennifer Dy is the subject of a feature by the Women in Machine Learning group. Read the feature to learn more about the work Professor Dy is doing and how it connects health, affective science, and climate science.

Sep 24, 2015

Big Data Alternative Clustering

ECE Professors Jennifer Dy & David Kaeli, and CEE Associate Professor April Gu were awarded a $860K NSF grant for “Exploring Analysis of Environment and Health Through Multiple Alternative Clustering”

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