Lam M. Nguyen

Overview

Lam M. Nguyen

Title

Staff Research Scientist; Master Inventor

Location

IBM Research - Yorktown Heights Yorktown Heights, NY USA

Bio

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 and the paper "A Hybrid Stochastic Optimization Framework for Composite Nonconvex Optimization" (SGD-SARAH) was selected as a winner of the 2022 Pat Goldberg Memorial Best Paper competition.

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". Dr. Nguyen also serves as a Panelist for National Science Foundation (NSF).

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.

Full list of publications

Academic Services:

  • Action Editor / Associate Editor: Journal of Machine Learning Research (2022 - Present), Machine Learning (2021 - Present), IEEE Transactions on Neural Networks and Learning Systems (2022 - Present), Journal of Optimization Theory and Applications (2022 - Present), Neural Networks (2022).
  • Area Chair / Meta-Reviewer / Senior Program Committee: ICML (2020, 2021, 2022, 2023, 2024), NeurIPS (2022, 2023), ICLR (2021, 2022, 2023, 2024), AISTATS (2021, 2022, 2023, 2024), UAI (2022, 2023), CVPR (2023, 2024), AAAI (2022).
  • Organizing Committee: Journal Chair (NeurIPS 2023), Workshop Organizer (NFFL NeurIPS 2021, MLmDS AAAI 2023)
  • Grant Reviewer: National Science Foundation, AI Singapore Research Programme.
  • Reviewer / Program Committee: ICML, NIPS/NeurIPS, ICLR, AISTATS, COLT, UAI, AAAI, IJCAI, CVPR, ICCV, ECCV.
  • Reviewer: Journal of Machine Learning Research, Mathematical Programming, SIAM Journal on Optimization, SIAM Journal on Numerical Analysis, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Signal Processing, Artificial Intelligence, Optimization Methods and Software, SIAM Journal on Mathematics of Data Science.

IBM Activities:

  • Champion, International Conference on Machine Learning (ICML): 01/2022 - Present
  • Member, Invention Development Team (IDT): 11/2021 - Present
  • Champion, Professional Interest Community (PIC) - Learning: 07/2021 - Present
  • Member, Research AI Pillar Accomplishment Committee: 2022
  • Reviewer, 2021 Pat Goldberg Memorial Best Paper Competition: 2022
  • Reviewer, IBM Ph.D. Fellowships: 2020

MIT-IBM Projects:

  • Principal Investigator, "Safe Learning for Time Series Problems: Data, Structure and Optimization": 01/2023 - 12/2025
  • Principal Investigator, "Safe AI Certification": 01/2022 - 12/2022
  • Principal Investigator, "Safety Structures, Certification, and Training for AI in the Feedback Loop": 01/2021 - 12/2021
  • Co-Principal Investigator, "Hierarchical Disentangled Representations for Scalable Multi-agent Reinforcement Learning": 09/2020 - 09/2021

IBM Research Accomplishments:

  • Research Contributions to Time Series Foundation Models (A-level), 2023
  • Federated Learning Security and Privacy (O-level), 2022
  • Dynamic Approaches for Machine Learning (A-level), 2022
  • Regression Optimization for Heavy Processing Industries (A-level), 2022
  • Combinatorial Sparsity for AI (A-level), 2022
  • Stochastic Gradient Methods: Theory and Applications (A-level), 2021
  • SROM: Smarter Resource & Operations Management (A-level), 2019

Honors & Awards:

  • 2022 Pat Goldberg Memorial Best Paper Award, 2023
  • IBM 9th Plateau Invention Achievement Award, 2023
  • IBM Outstanding Technical Achievement Award, Dynamic Approaches for Machine Learning, 2023
  • IBM Outstanding Technical Achievement Award, Regression Optimization for Heavy Processing Industries, 2023
  • IBM Outstanding Technical Achievement Award, Federated Learning Security and Privacy, 2023
  • IBM Outstanding Technical Achievement Award, Combinatorial Sparsity for AI, 2023
  • IBM 8th Plateau Invention Achievement Award, 2023
  • IBM Master Inventor, 2022
  • IBM 7th Plateau Invention Achievement Award, 2022
  • IBM 6th Plateau Invention Achievement Award, 2022
  • IBM Outstanding Technical Achievement Award, Stochastic Gradient Methods: Theory and Applications, 2022
  • IBM 5th Plateau Invention Achievement Award, 2022
  • IBM 4th Plateau Invention Achievement Award, 2022
  • IBM 3rd Plateau Invention Achievement Award, 2021
  • IBM 2nd Plateau Invention Achievement Award, 2020
  • IBM Research Division Award, 2020
  • IBM Outstanding Technical Achievement Award, SROM: Smarter Resource & Operations Management, 2020
  • IBM 1st Plateau Invention Achievement Award, 2020
  • NeurIPS 2019 Top Reviewers, 2019
  • Elizabeth V. Stout Dissertation Award, Lehigh University, PA, USA, 2019
  • Van Hoesen Family Best Publication Award, Lehigh University, PA, USA, 2018
  • Dean’s Doctoral Fellowship (RCEAS), Lehigh University, PA, USA, 2016 - 2017
  • Beta Gamma Sigma (Academic Honor), McNeese State University, LA, USA, 2014

Publications

Patents

Top collaborators

SD
Subhro Das

Subhro Das

Research Staff Member, Master Inventor