portrait of Feng Bao

Feng Bao

Assistant Professor, Mathematics
University of Tennessee at Chattanooga

Professional Experiences

  • Assistant Professor,  Department of Mathematics
    The University of Tennessee at Chattanooga, TN, July 2016 - present 
  • Postdoctoral Research Associate, Computer Science and Mathematics Division
    Oak Ridge National Laboratory, TN, July 2014 - July 2016
  • Short Term Researcher, Computer Science and Mathematics Division
    Oak Ridge National Laboratory, TN, Summer 2013

Education

  • Ph.D. in Mathematics, August, 2014,  Auburn University, Auburn, AL, USA
  • M.S. in Probability and Statistics, June, 2009,  Shandong University, China
  • B.S. in Mathematics, June, 2006,  Zhejiang University (Chu Kochen honor class), China

Research Interests

  • Analysis and numerical solution for stochastic differential equations
  • Analysis and numerical solutions for stochastic particle differential equations
  • Data assimilation and inference for stochastic processes
  • Uncertainty quantification
  • Stochastic optimization

Teaching in 2016-2017

  • Multivariable Calculus
  • Calculus with Analytic Geometry III

Publications

  1. F. Bao, Y. Cao, X. Han and J. Li, "Efficient Particle Filtering for Stochastic Korteweg-De Vries Equations ", Stochastics and Dynamics, 1750008 17(2), 2017

  2. 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.

  3. 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.

  4. F. Bao, Y. Cao, C. Webster and G. Zhang, "An Efficient Meshfree Implicit Filter for Nonlinear Filtering Problems", International Journal for Uncertainty Quantication, 6(1), 19-33, 2016.

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

  6. 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 Quantication, 4(1), 413-445, 2016.

  7. B. Hu, Y. Cao, W. Zhao and F. Bao , "Identification of hydraulic conductivity distributions in density dependent flow fields of submarine groundwater discharge modeling using adjoint-state sensitivities ", SCIENCE CHINA Earth Sciences , 59(4): 770-779, 2016.

  8. 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.

  9. 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 Quantication, 2(1), pp.784-804, 2014.

  10. 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.

  11. F. Bao, Y. Cao and W. Zhao, "Numerical Solutions for Forward Backward Doubly Stochastic Differential Equations and Zakai Equations", International Journal for Uncertainty Quantication, 1(4), pp. 351-367, 2011.

Preprints

  1. K. Kang, V. Maroulas, I. Schizas and F. Bao , "Improved Distributed Particle Filters for Tracking in Wireless Sensor Network ", submitted.

  2. F. Bao and Y. Cao, "A Backward Doubly Stochastic Differential Equation Approach for Nonlinear Filtering Problems", submitted

  3. F. Bao, Y. Cao and X. Han, "Forward Backward Doubly Stochastic Differential Equations and Optimal Filtering of Diusion Processes", arxiv:1509.06352 

  4. F. Bao and V. Maroulas, "Adaptive Meshfree Backward SDE Filter", submitted.

Projects

  • ACcurate qUantied Mathematical mEthods for Neutron science (ACUMEN)
    Sponsored by: DOE -Advanced Scientific Computing Research (ASCR)
  • I-Math: An Interdisciplinary Math Training Platform
    Sponsored by: NSF