Lewen Zheng

I am a final-year PhD student in the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong. I am thrilled to be supervised by Prof. Dohyun Ahn, who is an expert in systemic risk in banking systems, stochastic simulation methodologies, and decision making under uncertainty.

My research primarily focuses on Monte Carlo simulation methodologies, their applications in the sell-side financial services including quantitative risk measurement and derivatives pricing, implications for regulatory practices such as systemic risk quantification, and in non-financial sectors such as network analysis. One of my ongoing projects considers the efficient estimation of risks related to rare-but-critical events under distributional uncertainty. 

Recently, I am also interested in studying multi-armed bandit problems, a subfield of reinforcement learning, with an emphasis on the best arm identification problems with high dimensional data. This is mainly motivated by healthcare applications, for example, a drug company searching for the most effective drug may want to use as few clinical trials as possible to cut costs.

Researches

• Efficient Simulation under Distributional Uncertainty (with D. Ahn), working paper, 2024.

• Best-Arm Identification With High-Dimensional Features (with D. Ahn and D. Shin), Proceedings of the 2024 Winter Simulation Conference, 2025.

• Conditional Importance Sampling for Convex Rare-Event Sets (with D. Ahn), Proceedings of the 2023 Winter Simulation Conference, 2024.

• Efficient Simulation for Polyhedral Expectations with Applications to Finance (with D. Ahn), Major revision under Mathematics of Operations Research, 2024. [SSRN]

• Efficient Simulation for Linear Programming under Uncertainty (with D. Ahn), Proceedings of the 2021 Winter Simulation Conference, 2022. [Video][pdf]

Presentation Videos