FRE Special Seminar: Luhao Zhang

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Luhao Zhang

Assistant Professor in the Department of Applied Mathematics and Statistics, Johns Hopkins University.

Title

Causality and Robustness: Applications of Causal Transport

Abstract

This talk investigates how causal transport can be used to study robustness, risk, and fairness in decision-making under uncertainty. We show how the information structure of a problem guides the comparison of probability distributions and constrains admissible perturbations. Causal and bicausal transport incorporate this structure through conditional independence restrictions on transport plans. We explore applications in contextual distributionally robust optimization, dynamic risk measures, and conditional fairness in machine learning. We discuss the associated dual representations, dynamic decompositions, and computational reformulations, illustrating how information constraints shape the modeling and analysis of decisions under uncertainty.

Bio

Luhao Zhang is an assistant professor in the Department of Applied Mathematics and Statistics at Johns Hopkins University. Before joining JHU, she was a postdoctoral research scientist in the Department of Industrial Engineering and Operations Research at Columbia University from 2023 to 2024. She completed her Ph.D. in Mathematics at the University of Texas at Austin in 2023. Her research lies on interdisciplinary topics that integrate stochastic analysis, mathematical finance, and robust optimization, with an emphasis on how to exploit information optimally for decision-making in stochastic and uncertain environments from modeling and quantitative aspects. Another recent research interest of hers is the mathematical foundation of generative AI and human-AI interactions.