FSU Mathematics
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Feng Bao Assistant Professor Department of Mathematics, Florida State University Email: bao@math.fsu.edu Office: LOVE Building 312
I am an assistant professor of mathematics at Florida State University. My research interests include analysis and numerical solutions for stochastic (partial) differential equations, data assimilation and stochastic inference, stochastic optimal control, uncertainty quantification, and mathematical foundations for machine learning.
Ph.D. in Mathematics, Auburn University, Auburn, USA M.S. in Mathematics, Shandong University, Shandong, China B.S. in Mathematics, Zhejiang University, Hangzhou, China
Florida State University, USA Assistant Professor, Department of Mathematics, 2018 - present University of Tennessee at Chattanooga, USA Assistant Professor, Department of Mathematics, 2016 - 2018 Oak Ridge National Laboratory, USA Postdoc, Division of Computational Science and Mathematics, 2014-2016
Applied Math Seminar: Stochastic Computing and Data Science Stochastic Computing and Optimization
- CAREER: An Efficient Computational Framework for Data Driven Feedback Control (DMS-2142672) NSF - CAREER Program (PI, $424,053) - Reliable and Efficient Machine Learning for Leadership Facility Scientific Data Analytics (DE-SC0022297) DOE - Advanced Scientific Computing Research (PI, $301,222) - Frameworks, Algorithms and Scalable Technologies for Mathematics (FASTMath-5) DOE - Advanced Scientific Computing Research (University PI, $345,471) - Computational Framework for Unbiased Studies of Correlated Electron Systems (CompFUSE) DOE - Advanced Scientific Computing Research (University PI, $225,000) - Accurate Quantified Mathematical Methods for Neutron and Experimental Sciences (ACUMEN) DOE - Advanced Scientific Computing Research (University PI, $180,914)
- Efficient Adaptive Backward SDE Methods for Nonlinear Filtering problems (DMS-1720222) NSF - Computational Mathematics Program (PI, $124,995)
- NSF CAREER Award, 2022 - ORAU Ralph E. Powe Junior Faculty Enhancement Award, 2017 - Winner of 37th SIAM SEAS Conference Student Paper Competition, 2013 - Don and Sandy Logan Fellowship, Auburn University, 2012-2013
- Current Ph.D. students: Siming Liang, Yunzheng Lyu, Azaryah Wilson, Zezhong Zhang, Hui Sun - Former Ph.D. students: Xin Li (2021), placement: data scientist at Citi Bank
- Foundations of Data Science - Discrete and Continuous Dynamical System - series S - Numerical Methods for Partial Differential Equations |
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1. Z. Zhang, R. Archibald, F. Bao, A PDE-based Adaptive Kernel Method for Solving Optimal Filtering Problems, Journal of Machine Learning for Modeling and Computing, to appear, 2022
2. O. Dyck, F. Bao, M. Ziatdinov, Ali Y. Nobakht, K. Law, A. Maksov, B.G. Sumpter, R. Archibald, S. Jesse, S.V. Kalinin, and D.B. Lingerfelt, Strain-Induced Asymmetry and Om-Site Dynamics of Silicon Defects in Graphene, Carbon Trends, 9, 100189, 2022
3. R. Archibald, F. Bao, Y. Cao, and H. Zhang, A Backward SDE Method for Uncertainty Quantification in Deep Learning, Discrete and Continuous Dynamical Systems - Series S, to appear, 2022
4. R. Archibald, and F. Bao, Kernel Learning Backward SDE filter for Data Assimilation, Journal of Computational Physics, 455, 111009, 2022
5. X. Li, F. Bao, and K. Gallivan, A Drift Homotopy Implicit Particle Filter Method for Nonlinear Filtering Problems, Discrete and Continuous Dynamical Systems - Series S, 15(4), 727-746, 2022
6. X. Xie, F. Bao, T. Maier, and C. Webster, Analytic Continuation of Noisy Data Using Adams Bashforth Residual Neural Network, Discrete and Continuous Dynamical Systems - Series S, 15(4), 877-892, 2022
7. N.G. Cogan, F. Bao, R. Paus, and A. Dobreva, Data Assimilation of Synthetic Data as a Novel Strategy for Predicting Disease Progression in Alopecia Areata, Mathematical Medicine and Biology: A Journal of the IMA, 06,14778602 2021
8. H. Sun, and F. Bao, Meshfree Approximation for Stochastic Optimal Control Problems, Communications in Mathematical Research, 37(3), pp. 387-420, 2021
9. F. Bao, Y. Cao, and J. Yong, Data Informed Solution Estimation for Forward Backward Stochastic Differential Equations, Analysis and Applications, 19(3), pp. 439-464, 2021
10. O. Dyck, M. Ziatdinov, S. Jesse, F. Bao, A.Y. Nobakht, A. Maksov, S. Shin, B.G. Sumpter, R. Archibald, K.J.H. Law, and S.V. Kalinin, Probing potential energy landscapes via electron-beam-induced single atom dynamics, Acta Materialia, 203, 116508, 2021
11. R. Archibald, F. Bao, J. Yong, and T. Zhou, An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems, Journal of Scientific Computing, 85-51, 2020
12. A.Y. Nobakht, O. Dyck, D.B. Lingerfelt, F. Bao, M. Ziatdinov, A. Maksov, B.G. Sumpter, R. Archibald, S. Jesse, S.V. Kalinin, and K.J.H. Law, Reconstruction of Effective potential from statistical analysis of dynamic trajectories, AIP Advances, 10(6), 065034, 2020
13. R. Archibald, F. Bao, and J. Yong, A Stochastic Gradient Descent Approach for Stochastic Optimal Control, East Asian Journal of Applied Mathematics, 10(4), 635-658, 2020
14. F. Bao, Y. Cao and X. Han, Forward Backward Doubly Stochastic Differential Equations and Optimal Filtering of Diffusion Processes, Communications in Mathematical Sciences, 18(3), 635-661, 2020
15. F. Bao and T. Maier, Stochastic Gradient Descent Algorithm for Stochastic Optimization in Solving Analytic Continuation Problems, AIMS Foundations of Data Science, 2(1), 1-17, 2020
16. F. Bao, R. Archibald and P. Maksymovych, Backward SDE Filter for Jump Diffusion Processes and Its Applications in Material Sciences, Communications in Computational Physics, (27), 589-618, 2020
17. R. Archibald, R. Bao and X. Tu, A Direct Filter Method for Parameter Estimation, Journal of Computational Physics, (398), 108871, 2019
18. F. Bao and Y. Cao, Adjoint Forward Backward Stochastic Differential Equations Driven by Jump Processes and Its Application to Nonlinear Filtering Problems, International Journal for Uncertainty Quantification, 9(2), 143-159, 2019
19. F. Bao, L. Mu and J. Wang, A Fully Computable Posteriori Error Estimation for the Stokes Equations on Polytopal Meshes, SIAM Journal on Numerical Analysis, 57(1), 458-477, 2019
20. O. Dyck, F. Bao, M. Ziatdinov, A. Y. Nobakht, S. Shin, K. Law, A. Maksov, B.G. Sumpter, R. Archibald, S. Jesse, and S.V. Kalinin, Leveraging Single Atom Dynamics to Measure the Electron-Beam-Induced Force and Atomic Potentials, Proceedings of Microscopy and Microanalysis, 24, pp. 96-97, 2018
21. X. Xie, F. Bao and C. Webster, Evolve Filter Stabilization Reduced-Order Model for Stochastic Burgers Equation, Fluids, 3(4), 3040084, 2018
22. C. Yang, D. Posny, F. Bao and J. Wang, A Multi-scale Cholera Model Linking Between-host and Within-host Dynamics, International Journal of Biomathematics, 11(3), 1850034, 2018.
23. F. Bao, Y. Cao and W. Zhao, A Backward Doubly Stochastic Differential Equation Approach for Nonlinear Filtering Problems, Communications in Computational Physics, 23(5), pp. 1573-1601, 2018.
24. K. Kang, V. Maroulas, I. Schizas and F. Bao, Improved Distributed Particle Filters for Tracking in Wireless Sensor Network, Computational Statistics and Data Analysis, 117: 90-108, 2018.
25. F. Bao and V. Maroulas, Adaptive Meshfree Backward SDE Filter, SIAM Journal on Scientific Computing, 39(6), A2664-A2683, 2017
26. F. Bao, Y. Cao, X. Han and J. Li, Efficient Particle Filtering for Stochastic Korteweg-De Vries Equations, Stochastics and Dynamics, 17(2),1750008, 2017.
27. F. Bao, R. Archibald, J. Niedziela, D. Bansal and O. Delaire, Complex Optimization for Big Computational and Experimental Neutron Datasets, Nanotechnology, 27(48), 484002, 2016.
28. F. Bao, Y. Tang, M. Summers, G. Zhang, C. Webster, V. Scarola and T.A. Maier, Fast and Efficient Stochastic Optimization for Analytic Continuation, Physical Review-B, 94: 125149, 2016.
29. F. Bao, R. Archibald, D. Bansal and O. Delaire, Hierarchical Optimization for Neutron Scattering Problems, Journal of Computational Physics, 315: 39-51, 2016.
30. F. Bao, Y. Cao, C. Webster and G. Zhang, An Efficient Meshfree Implicit Filter for Nonlinear Filtering Problems, International Journal for Uncertainty Quantification, 6(1), 19-33 2016.
31. F. Bao, Y. Cao, A. Meir and W. Zhao, A First Order Fully Discretized Numerical Algorithm for Backward Doubly Stochastic Differential Equations, SIAM/ASA Journal on Uncertainty Quantification, 4(1), 413-445, 2016.
32. B. Hu, Y. Cao, W. Zhao and F. Bao, Identification of hydraulic conductivity distributions in density dependent flow fields of submarine groundwater discharge modelling using adjoint-state sensitivities, SCIENCE CHINA Earth Sciences, 59(4): 770-779, 2016.
33. F. Bao, Y. Cao and W. Zhao, A First Order Semi-Discrete Algorithm for Backward Doubly Stochastic Differential Equations, Discrete and Continuous Dynamical Systems - Series B, 2(5), pp. 1297-1313, 2015.
34. F. Bao, Y. Cao, C. Webster and G. Zhang, A Hybrid Sparse-Grid Approach for Nonlinear Filtering Problems Based on Adaptive-Domain of the Zakai Equation Approximations, SIAM/ASA Journal on Uncertainty Quantification, 2(1), pp.784-804, 2014.
35. F. Bao, Y. Cao and X. Han, An Implicit Algorithm of Solving Nonlinear Filtering Problems, Communications in Computational Physics, 16(2), pp. 382-402, 2014.
36. F. Bao, Y. Cao and W. Zhao, Numerical Solutions for Forward Backward Doubly Stochastic Differential Equations and Zakai Equations, International Journal for Uncertainty Quantification, 1(4), pp. 351-367, 2011.