1. M. Yin, E. Zhang, Y. Yu, G.E. Karniadakis, “Interfacing Finite Elements with Deep Neural Operators for Fast Multiscale Modeling of Mechanics Problems”, Computer Methods in Applied Mechanics and Engineering, (2022): 115027.

  2. M. Yin, E. Ban, E. Zhang, B. Rego, C. Cavinato, J.D. Humphrey, G.E. Karniadakis, “Simulating progressive intramural damage leading to aortic dissection using an operator-regression neural network”, Journal of the Royal Society Interface 19.187 (2022): 20210670.

  3. S. Goswami, M. Yin, Y. Yu, G.E. Karniadakis, “A physics-informed variational DeepONet for predicting the crack path in brittle materials”, Computer Methods in Applied Mechanics and Engineering 391 (2022): 114587.

  4. S. Cai, Z. Mao, Z. Wang, M. Yin, G.E. Karniadakis, “Physics-informed neural networks in fluid mechanics: A review”, Acta Mechanica Sinica (2022): 1-12.

  5. A. Blumers, M. Yin, Y. Hasegawa, Z. Li, and G.E. Karniadakis. “Supervised parallel-in-time algorithm for long-time Lagrangian simulations of stochastic dynamics: Application to blood flow in zebrafish”, Computational Mechanics 68.5 (2021): 1131-1152.

  6. M. Yin, X. Zheng, J.D. Humphrey, G.E. Karniadakis, “Non-invasive inference of thrombus material properties with physics-informed neural networks.” Computer Methods in Applied Mechanics and Engineering 375 (2021): 113603.

  7. E. Zhang, M. Yin, G.E. Karniadakis, “Physics-Informed Neural Networks for Nonhomogeneous Material Identification in Elasticity Imaging”, AAAI Conference (2020).

  8. M. Yin}, A. Yazdani, and G.E. Karniadakis. “One-dimensional modeling of fractional flow reserve in coronary artery disease: Uncertainty quantification and Bayesian optimization.” Computer Methods in Applied Mechanics and Engineering, 353 (2019): 66-85.

  9. D. Hopper, D. Jaganathan, J. Orr, J. Shi, F. Simeski, M. Yin, J.T.C. Liu, “Heat Transfer in Nanofluid Boundary Layer Near Adiabatic Wall.” Journal of Nanofluids 7.6 (2018): 1297-1302.

  10. M. Yin, J. Kou, W. Zhang, “A reduced-order aerodynamic model with high generalization capability based on neural network”, Acta Aerodynamica Sinica 35.02 (2017): 205-213.

  11. J. Kou, W. Zhang, and M. Yin, “Novel Wiener models with a time-delayed nonlinear block and their identification.” Nonlinear Dynamics 85.4 (2016): 2389-2404.