Luhao Zhang

Department of Mathematics
The University of Texas at Austin
2515 Speedway, PMA 8.100
Austin, TX 78712, USA

About me

I am currently a doctoral student in the Department of Mathematics at the University of Texas at Austin. My research lies at the intersection of data-driven decision making under uncertainty, stochastic and robust optimization, and machine learning. Specifically,

My Ph.D. advisor is Prof. Thaleia Zariphopoulou. My doctoral committee members include Profs. Rui Gao, Irene M. Gamba, Mihai Sirbu, and Stathis Tompaidis.

I received my bachelor degree in Mathematics and Applied Mathematics (Honors Program) at Xi’an Jiaotong University in China, where I was also a student of the Speical Class for the Gifted Young before my undergraduate study.



  1. Luhao Zhang, Jincheng Yang, Rui Gao. Optimal Robust Policy for Feature-Based Newsvendor (2022), Management Science, forthcoming.

  2. Luhao Zhang, Mohsen Ghassemi, Ivan Brugere, Alan Mishle, Niccolo Dalmasso, Vamsi Potluru, Tucker Balch, Manuela Veloso. Conditional Demographic Parity Through Optimal Transport (2022), NeurIPS Workshop on Algorithmic Fairness through the Lens of Causality and Privacy.


  1. Luhao Zhang, Jincheng Yang, Rui Gao. A Simple and General Duality Proof for Wasserstein Distributionally Robust Optimization (2022), under review for Management Science.

  2. Jincheng Yang*, Luhao Zhang*, Ningyuan Chen, Rui Gao, Ming Hu. Decision-making with Side Information: A Causal Transport Robust Approach (2022), to be submitted to Operations Research.

  3. Renyuan Xu*, Thaleia Zariphopoulou*, Luhao Zhang*. Decision Making with Learning and Opportunity to Reverse (2022), to be submitted to Operations Research.

  4. * indicates alphabetical order.

Teaching & Services


I am interesting in teaching a wide range of courses, including different topics in probability, statistics, and optimization. I have taught several topics as follows:

Professional Services

Referee for: Session chair for:

Directed Reading Program

The Directed Reading Program is an RTG program that pairs undergraduate students with graduate student mentors to undertake independent projects in mathematics.


Industry Experience & Skills

Industry Experience

Programming Languages

I have been teaching the following languages and their applications in Numerical Analysis and Applied Statistics:


Awards & Fundings