Viet Anh NGUYEN

News

Recruitment

I am recruiting junior researchers at all ranks (undergraduate/Master’s/Ph.D. students, postdoctoral fellows or research assistants) working at the Chinese University of Hong Kong. The research areas of interest include ethical analytics, responsible AI, human-machine interactions, robustness, etc. The start date is flexible and the remuneration is attractive. To apply, please fill up this Google form or send your application package to my email address.

Biography

From 2019 until summer 2021, Viet Anh Nguyen was a postdoctoral researcher at Stanford University, working with Professor Jose Blanchet and Professor Yinyu Ye. Between summer 2021 and summer 2022, he was a research scientist in the Machine Learning and Deep Learning research group at VinAI Research, Vietnam.

Viet Anh Nguyen received his doctoral degree in Management of Technology from Ecole Polytechnique Federale de Lausanne in 2019, where he worked with Daniel Kuhn and Peyman Mohajerin-Esfahani.

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 also holds a Diplome d’Ingenieur (promotion Gustave Eiffel) from Ecole Centrale des Arts et Manufactures (Ecole Centrale de Paris). He graduated from the Swiss Program for Beginning Doctoral Students in Economics at the Study Center Gerzensee in 2014.

He is interested in very large-scale decision making under uncertainty, statistical optimization and machine learning with applications in energy systems, operations management, and data/policy analytics.

Publications

Journal Publications

Conference Publications

Preprints

• Wasserstein Distributionally Robust Gaussian Process Regression and Linear Inverse Problems, with Xuhui Zhang, Jose Blanchet, Youssef Marzouk and Sven Wang. Under review.

• Distributionally Robust Recourse Action, with Duy Nguyen and Ngoc Bui. Under review.

• Gradient Flows on the Feature-Gaussian Manifold, with Truyen Nguyen, Xinru Hua, Tam Le and Jose Blanchet. Under review.

Tutorials

• Statistical Analysis of Wasserstein Distributionally Robust Estimators, with Jose Blanchet and Karthyek Murthy. INFORMS TutORials in Operations Research, 2021.

• Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning, with Daniel Kuhn, Peyman Mohajerin Esfahani and Soroosh Shafiee. INFORMS TutORials in Operations Research, 2019. [Video].

If you find any technical/implementation error in our papers/codes, please inform me via email. Thank you!

Thesis

• Adversarial Analytics. Ph.D. thesis at Ecole Polytechnique Federale de Lausanne. 2019.

• Routing and Planning for The Last Mile Mobility System. Master thesis at National University of Singapore. 2012.

Awards & Scholarships

• First place, George Nicholson Student Paper Competition, INFORMS 2018.

• Best Teaching Assistant Award, Ecole Polytechnique Federale de Lausanne, 2018.

• Teaching Assistantship, National University of Singapore, 2010-2012.

• Eiffel Excellence Scholarship, 2008-2010.

• ASEAN Undergraduate Scholarship, National University of Singapore, 2006-2010.

Supervisions

• Hieu Nguyen. Research resident at VinAI Research.

• Ngoc Bui. Research resident at VinAI Research.

• Duy Nguyen. Research intern at VinAI Research.

• Hieu Vu. Research resident at VinAI Research. First position: CS PhD student at University of Iowa.

• Sirui Lin. PhD student at Stanford MS&E.

• Xuhui Zhang. PhD student at Stanford MS&E.

• Bahar Taskesen. PhD student at EPFL.

• Yves Rychener. Master student at EPFL, 2019. Project title: Distributionally robust shrinkage estimator.

• Andreas Bill. Master student at EPFL, 2017. Thesis title: Distributionally robust optimization of solar energy planning for Switzerland 2050.

Professional Service

• Reviewer for journals: Management Science, Operations Research, Mathematical Programming, Mathematics of Operations Research, SIAM Journal on Optimization, INFORMS Journal on Computing, European Journal of Operational Research, Automatica, IEEE Transactions on Signal Processing, IEEE Transactions on Automatic Control, IEEE Transactions on Power Systems, Operations Research Letters, Transportation Research: Part B and Part E, Computers & Industrial Engineering, Journal of Optimization Theory and Applications, Expert Systems with Applications, Energy Systems, Computational Optimization and Applications.

• Reviewer for conferences: SIAM SODA 2019, ACC 2019, IEEE CDC 2017/2019, NeurIPS 2020/2021, ICML 2021/2022, ICLR 2021/2022.

Collaborators

Signature

To Normality and Beyond!