Prof. Viet Anh Nguyen
Assistant Professor
B.Eng, M.Eng (National University of Singapore)
Diplome d’Ingenieur (Ecole Centrale Paris)
Ph.D. (Ecole Polytechnique Federale de Lausanne)
Research Interests:
* Ethical Analytics
* Data Science
* Operations Research and
_Management
* Responsible Decision
_Making under
_Uncertainty
Office: Room 806, William M.W. Mong Engineering Building
Tel: (852) 3943-8462
Email: nguyen@se.cuhk.edu.hk
Biography
Viet Anh Nguyen received his Ph.D. degree in Management of Technology from Ecole Polytechnique Federale de Lausanne (EPFL) in 2019. Before that, he received a Bachelor of Engineering and a Master of Engineering in Industrial and Systems Engineering from the National University of Singapore in 2011 and 2013, respectively. He graduated from the Swiss Program for Beginning Doctoral Students in Economics at the Study Center Gerzensee in 2014. He also holds the Diplome d’Ingenieur (Gustave Eiffel batch) from Ecole Centrale des Arts et Manufactures (Ecole Centrale de Paris).
Viet Anh Nguyen won First Place at the 2018 INFORMS George E. Nicholson Best Student Paper Award, and the Best Teaching Assistant Award from EPFL in 2018.
He is interested in ethical decision making under uncertainty, statistical optimization and machine learning with applications in energy systems, operations management, and data/policy analytics.
Selected Publications
N. Bui, D. Nguyen and V. A. Nguyen, “Counterfactual plans under distributional ambiguity,” in International Conference on Learning Representations (ICLR), 2022.
H. Vu, T. Tran, M.-C. Yue and V. A. Nguyen, “Distributionally robust fair principal components via geodesic descents,” in International Conference on Learning Representations (ICLR), 2022.
D. Nguyen, N. Bui, D. Nguyen, M.-C. Yue and V. A. Nguyen, “Robust Bayesian recourse,” in Conference on Uncertainty in Artificial Intelligence (UAI), 2022.
T. Le, T. Nguyen, D. Phung and V. A. Nguyen, “Sobolev transport: A scalable metric for probability measures with graph metrics,” in International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.
V. A. Nguyen, S. Shafieezadeh-Abadeh, P. Mohajerin Esfahani and D. Kuhn, “Bridging Bayesian and minimax mean square error estimation via Wasserstein distributionally robust optimization,” forthcoming, Mathematics of Operations Research.
V. A. Nguyen, D. Kuhn, and P. Mohajerin Esfahani, “Distributionally robust inverse covariance estimation: The Wasserstein shrinkage estimator,” Operations Research, vol. 70, no. 1, pp. 490 – 515, 2021. First place, George E. Nicholson Student Paper Competition, INFORMS 2018.
C. Ordoudis, V. A. Nguyen, D. Kuhn and P. Pinson, “Energy and reserve dispatch with distributionally robust joint chance constraints,” Operations Research Letters, vol. 49, no. 3, pp. 291 – 299, 2021.
T. Le, T. Nguyen, M. Yamada, J. Blanchet and V. A. Nguyen, “Adversarial regression with doubly non-negative weighting matrices,” in Advances in Neural Information Processing Systems (NeurIPS), 2021.
B. Taskesen, M.-C. Yue, J. Blanchet, D. Kuhn, and V. A. Nguyen, “Sequential domain adaptation by synthesizing distributional robust experts,” in Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. Oral presentation, top 3% of submissions.
N. Si, K. Murthy, J. Blanchet and V. A. Nguyen, “Testing group fairness via optimal transport projections,” in Proceedings of the 38th International Conference on Machine Learning (ICML), 2021.
R. Vreugdenhil, V. A. Nguyen, A. Eftekhari, P. Mohajerin Esfahani, “Principal component hierarchy for sparse quadratic programs,” in Proceedings of the 38th International Conference on Machine Learning (ICML), 2021.
B. Taskesen, J. Blanchet, D. Kuhn, and V. A. Nguyen, “A statistical test for probabilistic fairness,” at ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2021.
J. Blanchet, K. Murthy and V. A. Nguyen, “Statistical analysis of Wasserstein distributional robust estimators,” INFORMS TutORials in Operations Research, pp. 227 – 254, 2021.
V. A. Nguyen, F. Zhang, J. Blanchet, E. Delage, and Y. Ye, “Distributionally robust local nonparametric conditional estimation,” in Advances in Neural Information Processing Systems (NeurIPS), 2020.
V. A. Nguyen, X. Zhang, J. Blanchet, and A. Georghiou, “Distributionally robust parametric maximum likelihood estimation,” in Advances in Neural Information Processing Systems (NeurIPS), 2020.
V. A. Nguyen, N. Si, and J. Blanchet, “Robust Bayesian classification using an optimistic score ratio,” in Proceedings of the 37th International Conference on Machine Learning (ICML), 2020.
D. Kuhn, P. Mohajerin Esfahani, V. A. Nguyen, and S. Shafieezadeh-Abadeh, “Wasserstein distributionally robust optimization: Theory and applications in machine learning,” INFORMS TutORials in Operations Research, pp. 130–166, 2019.
V. A. Nguyen, S. Shafieezadeh-Abadeh, M.-C. Yue, D. Kuhn, and W. Wiesemann, “Optimistic distributionally robust optimization for nonparametric likelihood approximation,” in Advances in Neural Information Processing Systems (NeurIPS), 2019.
V. A. Nguyen, S. Shafieezadeh-Abadeh, M.-C. Yue, D. Kuhn, and W. Wiesemann, “Calculating optimistic likelihoods using (geodesically) convex optimization,” in Advances in Neural Information Processing Systems (NeurIPS), 2019.
S. Shafieezadeh-Abadeh, V. A. Nguyen, D. Kuhn, and P. Mohajerin Esfahani, “Wasserstein distributionally robust Kalman filtering,” in Advances in Neural Information Processing Systems (NeurIPS), 2018. Spotlight presentation, top 5% of submissions.
V. A. Nguyen, J. Jiang, K. Ng, and K. Teo, “Satisficing measure approach for vehicle routing problem with time windows under uncertainty,” European Journal of Operational Research, vol. 248, no. 2, pp. 404 – 414, 2016.
A. Kumar, V. A. Nguyen and K. M. Teo, “Commuter cycling policy in Singapore: A farecard data analytics based approach,” Annals of Operations Research, vol. 236, pp. 57 – 73, 2016.