姓名： 蒲俊才 职称： 讲师 学历： 博士研究生
专业： 应用数学 邮箱：pujuncai@swufe.edu.cn
办公地址：通博楼B205
教育背景
2019.9-2023.7 华东师范大学 应用数学 理学博士
2016.9-2019.7 上海理工大学 应用数学 理学硕士
2012.9-2016.7 山西大同大学 数学与应用数学 理学学士
研究方向
可积系统，机器学习-可积深度学习算法
工作经历
2023.7-2025.7 北京应用物理与计算数学研究所 计算数学 博士后
2025.7-至今 西南财经大学 数学学院 讲师
代表性论文
[1] Pu Juncai, Chen Yong. Lax pairs informed neural networks solving integrable systems, Journal of Computational Physics, 2024, 510：113090.
[2] Pu Juncai, Chen Yong. Darboux transformation-based LPNN generating novel localized wave solutions, Physica D: Nonlinear Phenomena, 2024, 467: 134262.
[3] Pu Juncai, Chen Yong. Complex dynamics on the one-dimensional quantum droplets via time piecewise PINNs, Physica D: Nonlinear Phenomena, 2023, 454: 133851.
[4] Pu Juncai, Chen Yong. Data-driven forward-inverse problems for Yajima-Oikawa system using deep learning with parameter regularization, Communications in Nonlinear Science and Numerical Simulation, 2023, 118: 107051.
[5] Pu Juncai, Chen Yong. Double and triple-pole solutions for the third-order flow equation of the Kaup-Newell system with zero/nonzero boundary conditions, Journal of Mathematical Physics, 2023, 64: 103502.
[6] Pu Juncai, Chen Yong. Data-driven vector localized waves and parameters discovery for Manakov system using deep learning approach, Chaos, Solitons & Fractals, 2022, 160: 112182.
[7] Pu Juncai, Chen Yong. Integrability and exact solutions of the (2+1)-dimensional KdV equation with Bell polynomials approach, Acta Mathematicae Applicatae Sinica-English Series, 2022, 38: 861-881.
[8] Pu Juncai, Li Jun, Chen Yong. Solving localized wave solutions of the derivative nonlinear Schrödinger equation using an improved PINN method, Nonlinear Dynamics, 2021, 105: 1723-1739.
[9] Pu Juncai, Li Jun, Chen Yong. Soliton, breather, and rogue wave solutions for solving the nonlinear Schrödinger equation using a deep learning method with physical constraints, Chinese Physics B, 2021, 30: 060202.
[10] Pu Juncai, Peng Weiqi, Chen Yong. The data-driven localized wave solutions of the derivative nonlinear Schrödinger equation by using improved PINN approach, Wave Motion, 2021, 107: 102823.
主持项目
[1] 中国博士后科学基金第17批特别资助，2024T171175，主持
[2] 中国博士后科学基金第75批面上资助，2024M754242，主持
