Lam M. Nguyen  Lam M. Nguyen photo         

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Research Staff Member
Thomas J. Watson Research Center, Yorktown Heights, NY USA
  

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Professional Associations

Professional Associations:  INFORMS  |  SIAM Optimization Activity Group

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More information:  Personal Website

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I am a Research Staff Member (Research Scientist) at IBM Research AI, Thomas J. Watson Research Center working in the intersection of Optimization and Machine Learning/Deep Learning. I am also serving as an Editor for Machine Learning and Neural Networks journals, an Area Chair for ICML, ICLR, AAAI, and AISTATS conferences, and a member of Editorial Board for Journal of Machine Learning Research, Machine Learning, and Neural Networks. Here is my CV.

I got my Ph.D. degree in the Department of Industrial and Systems Engineering at Lehigh University in 2018. I was working with Dr. Katya Scheinberg and Dr. Martin Takáč in the area of Large Scale Optimization for Machine Learning and Stochastic Optimization. I have proposed a new algorithm for machine learning problems called SARAH (which is named after my daughter's name Sarah H. Nguyen) for solving convex and nonconvex large scale optimization problems. This paper is published in The 34th International Conference on Machine Learning (ICML 2017). During my Ph.D., I was also working with Dr. Alexander Stolyar in the area of Applied Probability, Stochastic Models and Optimal Control. I have won the 2019 P.C. Rossin College of Engineering and Applied Science Elizabeth V. Stout Dissertation Award.

I was born in Hanoi, Vietnam, but grew up in Moscow, Russia. I got my Bachelor degree in Applied Mathematics and Computer Science from Faculty (Department) of Computational Mathematics and Cybernetics, Lomonosov Moscow State University in 2008 under the supervision of Prof. Vladimir I. Dmitriev. I also received my M.B.A. degree from McNeese State University, Louisiana in 2013. Moreover, I was a Software Engineer at FPT Software Company.

I am very open to collaboration with highly motivated researchers!

Fields of interest:

  • Design and Analysis of Learning Algorithms
  • Optimization for Representation Learning
  • Federated Learning
  • Deep Reinforcement Learning
  • Explainable AI

Academic Services:

  • Action Editor / Associate Editor: Machine Learning, Neural Networks.
  • Area Chair / Meta-Reviewer / Senior Program Committee: ICML (2020, 2021), ICLR (2021, 2022), AISTATS (2021, 2022), AAAI (2022).
  • 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.
  • Editorial Board Member: Journal of Machine Learning Research, Machine Learning, Neural Networks.