方礼冬
讲师,硕士生导师
地址:红瓦楼923
邮箱:ldfang.sjtu@gmail.com
研究领域
{ multiscale modeling, reduced-order modeling, machine learning-based modeling, and simulation } of { crystalline solid, liquid crystals, and complex fluid }
教育经历

1Fang, L., Majumdar, A., & Zhang, L. (2020). Surface, size and topological effects for some nematic equilibria on rectangular domains. Mathematics and Mechanics of Solids, 25(5), 1101-1123.

2Fang, L., & Zhang, L. Blended Ghost Force Correction Method for 3D Crystalline Defects. Commun. Comput. Phys., 29(4), 1246-1272.

3Fang, L., Ge, P., Zhang, L. E, W., & Lei, H. (2022). DeePN^2: A Deep Learning-Based Non-Newtonian Hydrodynamic Model. Journal of Machine Learning, 1(1), 114-140.

4Liu, P., Fang, L., Wang, Y., Zhang, L., & Yang, Q. (2026). Concurrent Atomistic-Continuum Coupling via Physics-Informed Neural Networks with Adaptive Energy Weighting and Direct Boundary Encoding. Applied Mathematical Modelling, 116931.

工作经历

2024/12至今,上海财经大学,数学学院,讲师

学术交流
科研项目
科研奖励
代表性成果

1Fang, L., Majumdar, A., & Zhang, L. (2020). Surface, size and topological effects for some nematic equilibria on rectangular domains. Mathematics and Mechanics of Solids, 25(5), 1101-1123.

2Fang, L., & Zhang, L. Blended Ghost Force Correction Method for 3D Crystalline Defects. Commun. Comput. Phys., 29(4), 1246-1272.

3Fang, L., Ge, P., Zhang, L. E, W., & Lei, H. (2022). DeePN^2: A Deep Learning-Based Non-Newtonian Hydrodynamic Model. Journal of Machine Learning, 1(1), 114-140.

4Liu, P., Fang, L., Wang, Y., Zhang, L., & Yang, Q. (2026). Concurrent Atomistic-Continuum Coupling via Physics-Informed Neural Networks with Adaptive Energy Weighting and Direct Boundary Encoding. Applied Mathematical Modelling, 116931.