![Yinan Wang](/sites/default/files/styles/large/public/2023-02/Wang-Yinan.jpeg?itok=dggaTFsV)
Assistant Professor, Industrial and Systems Engineering
Physics-informed stochastic surrogate modeling for high-fidelity simulation, reinforcement-learning-based optimization for manufacturing process optimization, data-driven defective identification and quality improvement
1. Wang, Y., Sun, W., Jin, J., Kong, Z. and Yue, X., 2022+. MVGCN: Multi-view Graph Convolutional Neural Network for Surface Defect Identification using 3D Point Cloud. ASME Transactions Journal of Manufacturing Science and Engineering, 145(3): 031004.
2. Wang, Y., Guo, W.G. and Yue, X., 2022. Tensor decomposition to compress convolutional layers in deep learning. IISE Transactions, 54(5), pp.481-495.
3. Wang, Y., Wang, K., Cai, W. and Yue, X., 2022. NP-ODE: Neural process aided ordinary differential equations for uncertainty quantification of finite element analysis. IISE Transactions, 54(3), pp.211-226.
4. Wang, Y., Oyen, D., Guo, W., Mehta, A., Scott, C., Panda, N., Fernandez-Godino, G., Srinivasan, G. and Yue, X., 2021. StressNet - Deep learning to predict stress with fracture propagation in brittle materials. NPJ Material Degradation 5, 6.
5. Wang, R., Wang, Y.#, Devadiga, S., Perkins, I., Kong, Z.J. and Yue, X., 2021. Structured-light three-dimensional scanning for process monitoring and quality control in precast concrete production. PCI Journal, 66(6), pp.17-32.
(#: co-first author)