Dr. Wang Songhao joined the Business School of Southern University of Science and Technology in 2021 as an assistant professor. He obtained his Ph.D. degree in Industrial Systems Engineering and Management from National University of Singapore in 2020. Before joining Sustech, he worked as an AI researcher in Noah’s Ark Lab, Huawei Hong Kong research center. His main research areas are operations research, simulation optimization, Bayesian optimization, statistical modeling and machine learning. His papers are accepted by top journals in operations research like INFORMS Journal on Computing.

Educational Background:

Ph.D., Industrial Systems Engineering and Management, National University of Singapore, 2015-2020

B.S., Theoretical and Applied Mechanics, University of Science and Technology of China, 2011-2015

Research Interest：

operations research, simulation optimization, Bayesian optimization, statistical modeling and machine learning

Journal Papers:

1. Songhao Wang, Szu Hui Ng, and William B. Haskell. A multi-level simulation optimization approach for quantile functions. To appear in INFORMS Journal on Computing (UTD-24), 2020.

2. Qun Meng, Songhao Wang*, and Szu Hui Ng. Combined global and local optimization with Gaussian process models. To appear in INFORMS Journal on Computing (UTD-24), 2021.

3. Songhao Wang and Szu Hui Ng. Enhancing response predictions with a joint Gaussian process model for stochastic simulation models. ACM Transactions on Modeling and Computer Simulation (TOMACS) 30.1 (2020): 1-25.

4. Giulia Pedrielli, Songhao Wang, and Szu Hui Ng. An Extended two stage sequential optimization approach: generalization and asymptotic properties. European Journal of Operational Research 287.3 (2020): 929-945.