Ph.D., Industrial and Systems Engineering, Virginia Tech., 2022.
M.S., Electrical Engineering, Columbia University, 2019.
B.S., Electrical Engineering and Automation, Xi’an Jiaotong University, 2017.
Mary G. and Joseph Natrella Scholarship, American Statistical Association (ASA), 2022
Featured Article in ISE Magazine, Institute of Industrial and Systems Engineers (IISE), 2022
SPES + Q&P Best Student Paper Award, American Statistical Association (ASA), 2022
Educational Foundation Scholarship and Analysis Division Scholarship, International Society of Automation (ISA), 2021
Gilbreth Memorial Fellowship, Institute of Industrial and Systems Engineers (IISE), 2021
Data Mining & Decision Analytics (DMDA) Best Theoretical Paper Award, INFORMS, 2021
Finalist of Best Student Paper Award, Quality, Statistics & Reliability (QSR) Section, INFORMS, 2021
Best Poster Award, Manufacturing Science & Engineering Conference (MSEC), ASME, 2021
Yinan Wang, Kaiwen Wang, Wenjun Cai, Xiaowei Yue, 2022, “NP-ODE: Neural Process Aided Ordinary Differential Equations for Uncertainty Quantification of Finite Element Analysis”, IISE Transactions.
Yinan Wang, Weihong (Grace) Guo, Xiaowei Yue, 2022, “Tensor Decomposition to Compress Convolutional Layers in Deep Learning”, IISE Transactions.
Yinhua Liu, Wenzheng Zhao, Hongpeng Liu, Yinan Wang, Xiaowei Yue, 2022, “Coverage Path Planning for Robotic Quality Inspection with Control on Measurement Uncertainty”, IEEE/ASME Transactions on Mechatronics.
Yinan Wang, Diane Oyen, Weihong (Grace) Guo, Anish Mehta, Cory Scott, Nishant Panda, Giselle Fernandez-Godino, Gowri Srinivasan, Xiaowei Yue, 2021, “StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials”, NPJ Materials Degradation.
Kaiwen Wang, Yinan Wang, Xiaowei Yue, Wenjun Cai, 2021, “Multiphysics Modeling and Uncertainty Quantification of Tribocorrosion in Aluminum Alloys”, Corrosion Science.