Latest News
(Updated February 2023.)- February 2023: I am looking for PhD students with solid mathematical background to work on problems in optimization. Please email me if interested.
- October 2022: My co-author Huck Gutman and I received the INFORMS Optimization Society Young Researchers Prize for our paper on tangent subspace descent!
About Me
I am a Senior Lecturer in the Discipline of Business Analytics at The University of Sydney Business School.
My research focuses on data-driven optimization models and scalable algorithms for decision making problems under uncertainty.
Previously, I was a Postdoctoral Research Associate (from September 2019 to May 2020) at the University of Wisconsin-Madison, where I worked with Steve Wright. In May 2019, I completed my PhD at the Tepper School of Business, Carnegie Mellon University. I was very fortunate to be advised by Fatma Kılınç-Karzan.
In 2013, I completed my undergraduate degree in mathematics at the Australian National University.
You can find my CV here and email here.
Research
I employ techniques from large-scale optimization, machine learning and statistics to better understand the challenges and capabilities of decision making models under uncertainty.
I have also worked on the application a variety of optimization tools to choice modelling, portfolio selection, electronic trading, and solution design of IT services.
Preprints
- Non-smooth and Hölder-smooth Submodular Maximization. Duksang Lee, Nam Ho-Nguyen and Dabeen Lee. October 2022.
Journal articles
- An Online Convex Optimization-Based Framework for Convex Bilevel Optimization. Lingqing Shen, Nam Ho-Nguyen and Fatma Kılınç-Karzan. Articles in Advance Mathematical Programming.
- Strong Formulations for Distributionally Robust Chance-Constrained Programs with Left-Hand Side Uncertainty under Wasserstein Ambiguity. Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz and Dabeen Lee. Articles in Advance INFORMS Journal on Optimization.
- Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity. Nam Ho-Nguyen and Stephen J. Wright. Articles in Advance Mathematical Programming.
- Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds. David Huckleberry Gutman and Nam Ho-Nguyen. Articles in Advance Mathematics of Operations Research.
‣ INFORMS Optimization Society Young Researchers Prize 2022. - Risk Guarantees for End-to-End Prediction and Optimization Processes. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Management Science, 68(12), 8680-8698, 2022.
- Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty under Wasserstein Ambiguity. Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz and Dabeen Lee. Mathematical Programming, 196, 641–672, 2022.
- Cyclic Coordinate Descent in the Hölder Smooth Setting. David Huckleberry Gutman and Nam Ho-Nguyen. Operations Research Letters, 50(5), 458-462, 2022.
- Political Districting without Geography. J. Gerdus Benadè, Nam Ho-Nguyen, John N. Hooker. Operations Research Perspectives, 9, 2022.
- Dynamic Data-Driven Estimation of Non-Parametric Choice Models. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Operations Research, 69(4), 1228-1239, 2021.
- Exploiting Problem Structure in Optimization under Uncertainty via Online Convex Optimization. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Mathematical Programming, 177, 113-147, 2019.
- Online First-Order Framework for Robust Convex Optimization. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Operations Research, 66(6), 1670-1692, 2018.
‣ Honourable mention in the INFORMS Optimization Society Best Student Paper Prize 2018. - Primal–Dual Algorithms for Convex Optimization via Regret Minimization. Nam Ho-Nguyen and Fatma Kılınç-Karzan. IEEE Control Systems Letters, 2(2), 284-289, 2018.
Jointly accepted to the Conference on Decision and Control 2018. - A Second-Order Cone Based Approach for Solving the Trust-Region Subproblem and its Variants. Nam Ho-Nguyen and Fatma Kılınç-Karzan. SIAM Journal on Optimization, 27(3), 1485-1512, 2017.
Workshop proceedings
- Performance Evaluation of Iterative Methods for Solving Robust Convex Quadratic Problems. Christian Kroer, Nam Ho-Nguyen, George Lu and Fatma Kılınç-Karzan. Optimization for Machine Learning workshop at NeurIPS, 2017.
Work in progress
- Two-Stage Stochastic and Robust Optimization for Non-Adaptive Group Testing. Nam Ho-Nguyen.
- Black-Box Combinatorial Optimization with Monotonic Structure. Nam Ho-Nguyen, Giacomo Nannicini and Aly Megahed.
- Optimal Allocation Algorithms for Smart Order Routing with Cardinality and Integrality Constraints. Nam Ho-Nguyen and Michael Sotiropoulos.
- Iterative Methods for Ranking Students using Noisy Questions. J. Gerdus Benadè, Wolfgang Gatterbauer, Nam Ho-Nguyen, R. Ravi.
Awards
- The University of Sydney Business School Excellence in Research Award for Early Career Researchers 2022.
- INFORMS Optimization Society Young Researchers Prize 2022 (joint with Huck Gutman).
- The University of Sydney Business School Freda and Len Lansbury Early-Career Researcher Award 2021.
- Gerald L. Thompson Doctoral Dissertation Award in Management Science 2019.
- Honourable Mention in the INFORMS Optimization Society Best Student Paper Prize 2018 for our paper Online First-Order Framework for Robust Convex Optimization.
Teaching
- QBUS6820 Prescriptive Analytics: From Data to Decisions, S1 2023
- QBUS2310 Management Science, S1 2022, S1 2023
- BUSS4932 Advanced Optimization for Business, S1 2021, S2 2022
- QBUS6820 Business Risk Management, S2 2020, S2 2021
- QBUS1040 Foundations of Business Analytics, S2 2020, S1 2021, S1 2022