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庞国飞
副研究员
数学学院
计算数学系
电话：
邮箱：
guofei_pang@seu.edu.cn
地址：
图书馆549
邮编：
  • 基本信息
  • 研究成果
  • 项目与荣誉
  • 社会兼职
  • 庞国飞，男，中共党员，副研究员，硕士生导师，1987年生于安徽蚌埠，本科和博士分别毕业于河海大学数学系和工程力学系，曾在布朗大学应用数学部从事博士后研究工作。研究课题涉及计算数学、应用数学、统计和计算力学，主要研究方向为微分方程参数识别的统计（或机器）学习方法、不确定性量化、湍流数学力学建模、 分数阶微积分方程建模和数值算法、随机反问题以及计算流体动力学。 目前已在SIAM Journal on Scientific Computing、Journal of Computational Physics、Nature Machine Intelligence等计算数学/力学和机器学习领域的期刊上发表论文20余篇，参与撰写专著一部，书籍章节三篇，主持完成国家自然基金青年基金一项， 参与江苏省面上项目一项。****************** 讲授《高等数学》《数据结构与算法》《机器学习》《数学建模》等本科课程以及《数值分析》《求解偏微分方程的深度学习方法》等研究生课程。****************** 欢迎对我的研究方向感兴趣的同学报考我的硕士研究生。 请邮箱联系guofei_pang@seu.edu.cn。本人看似严肃却性格温和，长相老成却心态年轻，有同理心，喜欢倾听，希望与各位年轻同仁交个朋友，一起奋斗，健康快乐每一天，努力工作五十年。******************
    工作经历：2021/03 - 至今 东南大学数学学院 副研究员；2018/01 - 2020/08 布朗大学应用数学部 博士后；2015/12 - 2017/12 北京计算科学研究中心 博士后；2011/07 - 2012/06 香港大学机械工程系 研究助理。
    教育经历：2010/09 - 2015/11 河海大学工程力学系 博士；2006/09 - 2010/06 河海大学数学系 学士。


  • 期刊论文

    [30]Zhai, R., Yin, D., Pang, G.* (2023). A deep learning framework for solving forward and inverse problems of power-law fluids. Physics of Fluids, 35(9).

    [29]Deng, N., Cao, W.*, Pang, G. (2022). On numerical methods to second-order singular initial value problems with additive white noise. Journal of Computational and Applied Mathematics, 416, 114539.

    [28] Xin Zhao*, Xiaokai Nie, G. Pang, et al. Prior Distribution Estimation of Monitored Information in the Intensive Care Unit with the Hidden Markov Model and Decision Tree Methods. Journal of Healthcare Engineering, 2022.

    [27] Guofei Pang*, Wanrong Cao. (2021) Pseudo-Likelihood Estimation for Parameters of Stochastic Time-Fractional Diffusion Equations, Fractal and Fractional, 5(3), 129.

    [26] Lu, Lu, Pengzhan, Jin, Guofei Pang, Zhongqiang, Zhang, George, Karnaidakis*. (2021) Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators, Nature Machine Intelligence, 3(3),218-229.

    [25] Guofei Pang, Marta D'Elia*, Michael Parks, and George E. Karniadakis. "nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications." Journal of Computational Physics 422(2020):109760.

    [24] Mehta PavanPranjivan,Guofei Pang*, Fangying Song, and George Em Karniadakis. "Discovering a universal variable-order fractional model for turbulent Couette flow using a physics-informed neural network." Fractional Calculus and Applied Analysis 22, no. 6 (2019): 1675-1688.

    [23] Guofei Pang, Lu Lu, and George Em Karniadakis*. "fpinns: Fractional physics-informed neural networks." SIAM Journal on Scientific Computing 41.4 (2019): A2603-A2626.

    [22] Guofei Pang, Liu Yang, and George Em Karniadakis*. "Neural-net-induced Gaussian process regression for function approximation and PDE solution." Journal of Computational Physics 384 (2019): 270-288.

    [21] Yiran Xu, Jingye Li, Xiaohong Chen, and Guofei Pang*. "Solving fractional Laplacian visco-acoustic wave equations on complex-geometry domains using Grünwald-formula based radial basis collocation method." Computers & Mathematics with Applications (2019).

    [20]A. Lischke, G. Pang（共同一作), M. Gulian, F. Song, C. Glusa, X. Zheng, Z. Mao, W. Cai, M.M. Meerschaert, M. Ainsworth,and G.E. Karniadakis*. “What is the fractional Laplacian? A comparative review with new results.” Journal of Computational Physics 404 (2020): 109009. 

    [19] Guofei Pang, Paris Perdikaris, Wei Cai, and George Em Karniadakis. "Discovering variable fractional orders of advection–dispersion equations from field data using multi-fidelity Bayesian optimization." Journal of Computational Physics 348 (2017): 694-714.

    [18] Guofei Pang, Wen Chen*, and Zhuojia Fu. "Space-fractional advection–dispersion equations by the Kansa method." Journal of Computational Physics 293 (2015): 280-296.

    [17] Guofei Pang, Wen Chen*, and K. Y. Sze. "Gauss–Jacobi-type quadrature rules for fractional directional integrals." Computers & Mathematics with Applications 66.5 (2013): 597-607.

    [16] Guofei Pang, Wen, Chen*., & K. Y. Sze (2014). Differential quadrature and cubature methods for steady-state space-fractional advection-diffusion equations. Comput. Model. Eng. Sci, 97, 299-322.

    [15] Guofei Pang, and Wen Chen*. "Symmetric singular boundary method for potential problems with mixed boundary conditions." Engineering Analysis with Boundary Elements 56 (2015): 49-56.

    [14] Guofei Pang, Wen Chen*, and K. Y. Sze. "A comparative study of finite element and finite difference methods for two-dimensional space-fractional advection-dispersion equation." Advances in Applied Mathematics and Mechanics 8.1 (2016): 166-186.

    [13] 庞国飞, 陈文*, 张晓棣, & 孙洪广. (2015). 复杂介质中扩散和耗散行为的分数阶导数唯象建模. 应用数学和力学, (1000-0887), 36(11).

    [12] 庞国飞,陈文*. (2017). 基于 Riesz 势空间分数阶算子的非局部粘弹性力学元件. 固体力学学报, 38(1), 47-54.

    [11]Mamikon, Gulian*, and Guofei, Pang. "Stochastic Solution of Elliptic and Parabolic Boundary Value Problems for the Spectral Fractional Laplacian." arXiv preprint arXiv:1812.01206 (2018).

    [10] Chen Wen*, and Guofei Pang. "A new definition of fractional Laplacian with application to modeling three-dimensional nonlocal heat conduction." Journal of Computational Physics 309 (2016): 350-367.

    [9] 李源, 陈文*, 庞国飞. (2014). 应用分数阶导数模拟桩屏障对粘弹性 SH 波的隔离. 应用数学和力学, 35(9), 949-958.

    [8] Weiwei Li, Wen Chen*, and Guofei Pang. "Singular boundary method for acoustic eigenanalysis." Computers & Mathematics with Applications 72.3 (2016): 663-674.

    [7] Sun H., Liu X., Zhang Y., Pang Guofei, and Garrard, R. (2017). A fast semi-discrete Kansa method to solve the two-dimensional spatiotemporal fractional diffusion equation.Journal of Computational Physics, 345, 74-90.

    [6] Chen W., Fang J, Pang Guofei, and Holm S. (2017). Fractional biharmonic operator equation model for arbitrary frequency-dependent scattering attenuation in acoustic wave propagation. The Journal of the Acoustical Society of America, 141(1), 244-253.

    [5] Hei X., Chen W., Pang Guofei., Xiao R., and Zhang C. (2018). A new visco–elasto-plastic model via time–space fractional derivative. Mechanics of Time-Dependent Materials, 22(1), 129-141.


    书籍和书籍章节

    [4] Guofei Pang, and George Em Karniadakis. “Physics-informed learning machines for PDEs: Gaussian processes versus neural networks.” Emerging Frontiers in Nonlinear Science, 2020.

    [3] E Kharazmi, Z Mao, G Pang, M Zayernouri, GE Karniadakis. Fractional calculus and numerical methods for fractional PDEs . First Congress of Greek Mathematicians, 91-126, 2020

    [2] Guofei Pang, Wen Chen. “Comparison of two radial basis collocation methods for poisson problems with fractional Laplacian.” Handbook of Fractional Calculus with Applications. Volume 3: Numerical Methods, 2019

    [1] 参与撰写 《反常扩散的分数阶微分方程和统计模型》，科学出版社，2017


    软件著作权

    陈文、庞国飞、张晓棣，胡帅，非均质介质中声波衰减的数值模拟软件V1.0，申请号2015R11L031085

  • 项目经历

       

      1. 主持国家自然基金青年基金：分数阶导数对流-弥散方程参数识别的多重精度高斯过程回归算法（11701025），20万， 2018/01 - 2020/12。

      2. 主持东南大学学科攀升计划专项经费——理科专项，40万

      3. 主持海岸灾害及防护教育部重点实验室（河海大学）2022年度开放研究基金面上项目：基于神经网络的风暴潮漫滩模拟和风险评价， 4万

      4. 曾参与美国国防部Army Research Office (ARO) mission 

      (1) Multidisciplinary University Research Initiative， Army Research Office (ARO)（项目号 W911NF-18-1-0301）            

      (2) Fractional Partial Differential Equations ARO MURI Project: Fractional PDEs for Conservation Laws and Beyond: Theory, Numerics, and Applications （项目号：W911NF-15-1-0562）

     

    荣誉

      东南大学授课竞赛三等奖（2022-2023）

      东南大学优秀班主任（2022-2023）


    早期荣誉

      在河海大学求学期间曾获得的荣誉：

      国家奖学金

      研究生国家奖学金

      大学生数学建模竞赛全国一等奖

      美国大学生数学建模竞赛Meritorious Winner

      河海大学博士生特等奖学金



    邀请报告

     2018年4月, SIAM UQ18  mini-symposium “Stochastic modeling and methods in scientific computing”, Discovering Variable Fractional Orders of Advection Dispersion Equations from Field Data using Multi-fidelity Bayesian Optimization, Garden Grove, CA, USA.

     2019年2月, “Clements seminar at Southern Methodist University”, Physics-informed neural networks: A deep learning framework for solving forward and inverse problems of PDEs and fractional PDEs, Dallas, TX, USA.

     2019年5月,“ Physics in Machine Learning Workshop”, Physics informed Machine Learning, UC Bekerley, CA, USA.

     2019年11月,  The 2nd Annual Meeting of SIAM Texas-Louisiana Section, mini-symposium “Machine Learning for Solving PDEs and Inverse Problems”, Physics-informed neural networks for diffusion problems with unified nonlocal operator, Dallas, TX, USA



    教学经历

      2020年1月-2020年5月， 布朗大学本科课程， Introduction to numerical solution of differential equations, 布朗大学， 美国

      2017年6月， 随机计算和不确定性量化培训班， 授课，  北京计算科学研究中心， 中国



  • 1. Topic editor for the journal Fractal and Fractional.

    2. 中国工业与应用数学学会会员

    3. 指导研究生数学建模：国家二等奖  （2021）

    4. 指导国家级SRTP项目一项 （2022.06-2023.06）

    5. 东南大学2022-2023优秀班主任