Lam M. Nguyen is a Research Staff Member at IBM Research, Thomas J. Watson Research Center working in the intersection of Optimization and Machine Learning/Deep Learning. He is also the PI of ongoing MIT-IBM Watson AI Lab projects. 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 Machine Learning, Neural Networks, and IEEE Transactions on Neural Networks and Learning Systems journals, an Area Chair for ICML, NeurIPS, ICLR, AAAI, UAI, and AISTATS conferences, and a member of Editorial Board for Journal of Machine Learning Research. His current research interests include design and analysis of learning algorithms, optimization for representation learning, federated learning, reinforcement learning, time series, and trustworthy/explainable AI.