A Scalable MIP-based Method for Learning Optimal Multivariate Decision Trees
- Haoran Zhu
- Pavankumar Murali
- et al.
- NeurIPS 2020
Dr. Lam M. Nguyen is a Staff Research Scientist at IBM Research, Thomas J. Watson Research Center working in the intersection of Optimization and Machine Learning / Deep Learning. He is also a Principal Investigator of ongoing MIT-IBM Watson AI Lab projects and an IBM Master Inventor. At IBM Research, his work on "Stochastic Gradient Methods: Theory and Applications" was selected for 2021 IBM Research Accomplishments.
Dr. Nguyen received his B.S. degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University in 2008; M.B.A. degree from McNeese State University in 2013; and Ph.D. degree in Industrial and Systems Engineering from Lehigh University in 2018. Dr. Nguyen has extensive research experience in optimization for machine learning problems. He has published his work mainly in top AI/ML and Optimization publication venues, including ICML, NeurIPS, ICLR, AAAI, AISTATS, Journal of Machine Learning Research, and Mathematical Programming. He has been serving as an Action/Associate Editor for Journal of Machine Learning Research, Machine Learning, Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, and Journal of Optimization Theory and Applications; an Area Chair for ICML, NeurIPS, ICLR, CVPR, AAAI, UAI, and AISTATS conferences. Dr. Nguyen is also in the Organizing Committee for NeurIPS 2023. Moreover, he organized the AAAI 2023 workshop "When Machine Learning meets Dynamical Systems: Theory and Applications" and the NeurIPS 2021 workshop "New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership".
His current research interests include design and analysis of learning algorithms, optimization for representation learning, dynamical systems for machine learning, federated learning, reinforcement learning, time series, and trustworthy/explainable AI. Please see his personal website for more detailed information.
IBM Research Accomplishments:
Honors & Awards: