Kun Zhang currently is an Assistant Professor in Institute of Statistics and Big Data, Renmin University of China. He holds a bachelor degree in Mathematics and Applied Mathematics, master degree in Probability Theory from School of Mathematical Sciences, Beijing Normal University, and doctoral degree in Management Science from College of Business, City University of Hong Kong. His research interests include stochastic simulation, machine learning, financial engineering and risk management.

Publications:

（下划线为博士生，*表示通讯作者）

1. Hong-Fa Cheng, Kun Zhang^*. 2021. Non-nested estimators for the central moments of a conditional expectation and their convergence properties. Operations Research Letters, published online.

2. Kun Zhang, Guangwu Liu, Shiyu Wang. 2021. Bootstrap-based budget allocation for nested simulation. Operations Research, published online.

3. Li-Juan Cheng, Kun Zhang. 2017. Reflecting diffusion semigroup on manifolds carrying geometric flow. Journal of Theoretical Probability, 30(4), 1334-1368.

4. Guangwu Liu, Wen Shi, Kun Zhang. 2019. An upper confidence bound approach to estimating coherent risk measures. Proceedings of the 2019 Winter Simulation Conference, IEEE. pp.914-925.

5. Kun Zhang, Guangwu Liu, Shiyu Wang. 2017. Portfolio risk measurement via stochastic mesh. Proceedings of the 2017 Winter Simulation Conference, IEEE. pp.1796-1811.

6. Shiyu Wang, Guangwu Liu, Kun Zhang. 2017. A Misspecication Test for Simulation Metamodels. Proceedings of the 2017 Winter Simulation Conference, IEEE. pp.1938-1949.

Working Papers:

1. Kun Zhang and Guangwu Liu. 2021. Simulating conditional average value-at-risk. Under review in IIE Transactions.

2. Shiyu Wang, Guangwu Liu and Kun Zhang. 2021. A misspecication test for simulation metamodels.

3. Guangwu Liu, Bingfeng Zhang and Kun Zhang. 2021. Simulating bounds for conditional Value-at-Risk.

4. Hong-Fa Cheng, Kun Zhang. 2021. Constructing confidence intervals for nested simulation.