Integer Programming, Production Scheduling, Data-driven Optimization
Northeastern University, PhD in Systems Engineering.
Northeastern University, Bachelor in Control Theory and Engineering.
Dr. Wang Yuan joined the Shenzhen Big Data Research Institute in November 2022. He received his bachelor’s and PhD degrees in System Engineering from Northeastern University in 2013 and 2019 respectively. In 2019, he worked as an algorithm engineer (intern) at Huawei Noah's Ark Lab, where he was mainly responsible for algorithm research and development for Huawei's multi-factory production planning problems. From 2019 to 2022, he worked as a postdoctoral researcher at The Chinese University of Hong Kong (Shenzhen), focusing on data-driven optimization methods to solve multi-airport 4D trajectory planning problems in air traffic flow management.
 Wang Y, Luo X, Zhang F, et al. GPU-based model predictive control for continuous casting spray cooling control system using particle swarm optimization[J]. Control Engineering Practice, 2019, 84: 349-364.
 Wang Y, Luo X, Yu Y, et al. Evaluation of heat transfer coefficients in continuous casting under large disturbance by weighted least squares Levenberg-Marquardt method[J]. Applied Thermal Engineering, 2017, 111: 989-996.
 Cui H, Luo X, Wang Y. Scheduling of steelmaking-continuous casting process using deflected surrogate Lagrangian relaxation approach and DC algorithm[J]. Computers & Industrial Engineering, 2020, 140: 106271.
 Cui H, Luo X, Wang Y. Scheduling of steelmaking-continuous casting process with different processing routes using effective surrogate Lagrangian relaxation approach and improved concave–convex procedure[J]. International Journal of Production Research, 2021: 1-26.
 Yu Y, Luo X, Wang Y, et al. Estimation of boundary condition of two-dimensional nonlinear PDE with application to continuous casting[J]. Computers & Mathematics with Applications, 2020, 80(12): 3082-3097.
 Zhang Z, Wang Y, Liu C. Multihoming effect on the two-sided platform of second-hand cars[J]. Computers & Industrial Engineering, 2023: 109160.