Latest News(Updated August 2020.)
- July 2020: New preprint on distributionally robust chance constraints with Fatma Kılınç-Karzan, Simge Küçükyavuz and Dabeen Lee.
- June 2020: I am very excited to be joining the Discipline of Business Analytics at The University of Sydney Business School!
- May 2020: New preprint on adversarial classification with Steve Wright.
Since June 2020, I am a Lecturer in the Discipline of Business Analytics at The University of Sydney Business School.
My research focused 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. You can find a copy of my dissertation here.
In 2013, I completed my undergraduate degree in mathematics at the Australian National University.
You can find my CV here and email here.
I use 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.
- 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. July 2020.
- Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen and Stephen J. Wright. May 2020.
- Distributionally Robust Chance-Constrained Programs with Right-Hand Side Uncertainty under Wasserstein Ambiguity Nam Ho-Nguyen, Fatma Kılınç-Karzan, Simge Küçükyavuz and Dabeen Lee. March 2020.
- Coordinate Descent Without Coordinates: Tangent Subspace Descent on Riemannian Manifolds David Huckleberry Gutman and Nam Ho-Nguyen. December 2019.
- Risk Guarantees for End-to-End Prediction and Optimization Processes. Nam Ho-Nguyen and Fatma Kılınç-Karzan. June 2019.
- Dynamic Data-Driven Estimation of Non-Parametric Choice Models. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Forthcoming in Operations Research.
- Exploiting Problem Structure in Optimization under Uncertainty via Online Convex Optimization. Nam Ho-Nguyen and Fatma Kılınç-Karzan. Mathematical Programming Series A, 177(1), 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.
- 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
- 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.
- QBUS6820 Business Risk Management, Semester 2, 2020
- QBUS1040 Foundations of Business Analytics, Semester 2, 2020