Lam Nguyen

Lam M. Nguyen (or Lam Nguyen; Vietnamese: Nguyễn Minh Lâm, born October 22, 1986) is a Vietnamese-American computer scientist and applied mathematician known for his contributions to optimization algorithms for machine learning and notable for proposing and developing the SARAH stochastic recursive gradient method. He is a Research Scientist at the IBM Research, Thomas J. Watson Research Center, New York, USA, where his research focuses on the intersection of optimization and machine learning. He is an INFORMS Senior member and a member of the Beta Gamma Sigma honor society, one of the highest honors a business student can receive.

Education and career Nguyen earned a Bachelor of Science degree in Applied Mathematics and Computer Science from Lomonosov Moscow State University (2008) under the supervision of Vladimir Dmitriev His doctoral advisor was Katya Scheinberg.

He joined IBM Research in 2018 as a Research Scientist.

Research and contributions Nguyen's research centers on optimization methods for machine learning and stochastic optimization. He is recognized as the lead inventor of the SARAH (Stochastic Recursive Gradient) algorithm, introduced at ICML 2017, which has influenced a wide class of variance-reduced optimization methods. The SARAH algorithm has been included in graduate-level courses on stochastic optimization and machine learning at several research universities, including Princeton University and EPFL, where it is presented as a representative variance-reduction method in modern optimization curricula.

He is the co-editor of the book Federated Learning: Theory and Practice (Elsevier, 2024), which provides a unified treatment of the theoretical and practical aspects of federated learning.

Editorial and professional service Nguyen serves as an Action Editor for the Journal of Machine Learning Research and Machine Learning, and as an Associate Editor of the Journal of Optimization Theory and Applications. He has been in the Organizing Committee for the Conference on Neural Information Processing Systems (NeurIPS) 2023–2025,

Selected publications Nguyen, L. M. et al. (2017). "SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient." In Proceedings of ICML 2017. Nguyen, L. M. et al. (2024). Federated Learning: Theory and Practice. Elsevier.