Jennifer Dy
Professor at Northeastern University
COE Distinguished Professor, ECE Department
Director of AI Faculty, Institute for Experiential AI
Northeastern University
jdy (at) ece (dot) neu (dot) edu
Jennifer G. Dy is a COE Distinguished Professor at the Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, where she first joined the faculty in 2002. She received her M.S. and Ph.D. in 1997 and 2001 respectively from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, and her B.S. degree from the Department of Electrical Engineering, University of the Philippines, in 1993.
Her research spans both foundations in machine learning and its application to biomedical imaging, health, science and engineering, with research contributions in unsupervised learning, interpretable models, explainable AI, continual learning, dimensionality reduction, feature selection/sparse methods, learning from uncertain experts, active learning, Bayesian models, and deep representation learning. She is Director of AI Faculty at the Institute for Experiential AI, Director of the Machine Learning Lab and is a founding faculty member of the SPIRAL (Signal Processing, Imaging, Reasoning, and Learning) Center at Northeastern.
She received an NSF Career award in 2004. She has served or is serving as Secretary for the ICML Board (formerly, International Machine Learning Society), associate editor/editorial board member for the Journal of Machine Learning Research, Machine Learning journal, IEEE Transactions on Pattern Analysis and Machine Intelligence, organizing and or technical program committee member for premier conferences in machine learning, AI, and data mining (ICML, NeurIPS, ACM SIGKDD, AAAI, IJCAI, UAI, AISTATS, ICLR, SIAM SDM), Program Chair for SIAM SDM 2013, ICML 2018, AISTATS 2023, and AAAI 2024.
NEWS
Aug 5, 2024 | I’m happy to announce that two of our papers, Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions and Boundary-Aware Uncertainty for Feature Attribution Explainers were accepted into AISTATS (2024). |
---|---|
Feb 4, 2024 | I am glad to have received the COE Distinguished Faculty Award at Northeastern University. |
Jan 4, 2024 | I am honored to have been elected a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI). |
Sep 21, 2023 | I’m happy to announce that our paper SmoothHess was accepted into NeurIPS (2023). |
SELECTED PUBLICATIONS
2024
- In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 02–04 may 2024
- In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, 02–04 may 2024
2023
- In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023, 02–04 may 2023
- In International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA, 02–04 may 2023
2022
- In International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event, 02–04 may 2022
- In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022, New Orleans, LA, USA, June 18-24, 2022, 02–04 may 2022
- In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022, 02–04 may 2022
-
2021
- Medical Image Anal., 02–04 may 2021
- In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 02–04 may 2021
2020
- In 20th IEEE International Conference on Data Mining, ICDM 2020, Sorrento, Italy, November 17-20, 2020, 02–04 may 2020
- In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 02–04 may 2020