Nam Ho-Nguyen

Nam Ho-Nguyen is an Associate Professor in the Discipline of Business Analytics at the University of Sydney Business School. His research focuses on business analytics, operations research, optimisation, and adversarial machine learning. He is affiliated with the University of Sydney's Business School (BUS) department. His work involves stochastic, robust, and data-driven optimization techniques for decision-making under uncertainty. Prior to joining the University of Sydney, he was a postdoctoral research associate at the Wisconsin Institute for Discovery within the University of Wisconsin-Madison. He holds a PhD in Operations Research from the Tepper School of Business at Carnegie Mellon University and an Honours degree in Mathematics from the Australian National University.

Nam Ho-Nguyen is an operations research scholar at the University of Sydney, specializing in optimization under uncertainty and robust decision-making. His research focuses on developing advanced mathematical frameworks to address complex problems in operations research, including distributionally robust optimization, convex bilevel optimization, and online convex optimization. His work emphasizes risk guarantees, adversarial classification, and efficient algorithms for solving optimization problems with stochastic and adversarial constraints. He has contributed significantly to the development of projection-free methods and tangent subspace descent techniques for non-smooth and robust optimization. His research has applications in prediction, optimization, and strategic decision-making under uncertainty.