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FSU Mathematics


Feng Bao

Assistant Professor

Department of Mathematics, Florida State University

Email: bao@math.fsu.edu

Office: LOVE Building 312

 

 

Overview

 

 

 

I am an assistant professor in Department of Mathematics at Florida State University. My research interests include analysis and numerical solutions for stochastic differential equations, data assimilation and stochastic inferences, uncertainty quantification, and stochastic optimization.

 

 

Education

 

 

 

Auburn University, Auburn, USA

Ph.D. in Mathematics, 2014

Shandong University, Shandong, China

M.S. in Mathematics, 2009

Zhejiang University, Hangzhou, China

B.S. in Mathematics, 2006

 

 

Professional Experience

 

 

 

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

 

 

Teaching in Spring 2020

 

 

 

Calculus III

Special Topic Course: Stochastic Computing and Data Assimilation

 

Current Research projects

 

 

 

-       Computational Framework for Unbiased Studies of Correlated Electron Systems (CompFUSE)

DOE - Advanced Scientific Computing Research (Single University PI), 2017-2021

-       Efficient Adaptive Backward SDE Methods for Nonlinear Filtering problems

NSF - Computational Mathematics Program (DMS-1720222 PI), 2017-2020

-       Frameworks, Algorithms and Scalable Technologies for Mathematics (FASTMath)

DOE - Advanced Scientific Computing Research (Single University PI), 2018-2020

 

Honors and Awards

 

 

 

-       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

 

Publications

 

 

 

 

 

 

1.     R. Archibald, R. Bao and X. Tu, A Direct Filter Method for Parameter Estimation, Journal of Computational Physics, in press

2.     F. Bao, R. Archibald and P. Maksymovych, Backward SDE Filter for Jump Diffusion Processes and Its Applications in Material Sciences, Communications in Computational Physics, to appear

3.     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

4.     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

5.     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

6.     X. Xie, F. Bao and C. Webster, Evolve Filter Stabilization Reduced-Order Model for Stochastic Burgers Equation, Fluids, 3(4), 3040084, 2018

7.     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. 

8.     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. 

9.      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. 

10.   F. Bao and V. Maroulas, Adaptive Meshfree Backward SDE Filter, SIAM Journal on Scientific Computing, 39(6), A2664-A2683, 2017 

11.   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. 

12.   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. 

13.   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. 

14.   F. Bao, R. Archibald, D. Bansal and O. Delaire, Hierarchical Optimization for Neutron Scattering Problems, Journal of Computational Physics, 315: 39-51, 2016. 

15.   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. 

16.   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. 

17.   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. 

18.   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. 

19.   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. 

20.   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. 

21.   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.