Math @ Duke

Hongkai Zhao, Ruth F. DeVarney Distinguished Professor
My research interest is in computational and applied mathematics that includes modeling, analysis and developing numerical methods for problems arising from science and engineering. More specifically, I have worked on:
 numerical analysis and scientific computing;
 multiscale, multiphysics and multiphase problems in wave propagation, fluids, and materials;
 inverse problems related to medical and seismic imaging;
 computer vision and image processing.
My Google Scholar Citations Contact Info:
Office Location:   Office Phone:  (919) 6602800  Email Address:   Teaching (Fall 2023):
 MATH 375.01, LINEAR PROGRAMMING
Synopsis
 Physics 227, WF 01:25 PM02:40 PM
 MATH 561.01, NUMERICAL LINEAR ALGEBRA
Synopsis
 Physics 205, WF 03:05 PM04:20 PM
 MATH 757.01, LINEAR PROGRAMMING
Synopsis
 Physics 227, WF 01:25 PM02:40 PM
Teaching (Spring 2024):
 MATH 563.01, APPLIED COMPUTATIONAL ANALYSIS
Synopsis
 Physics 227, WF 03:05 PM04:20 PM
 Office Hours:
 Wednesday 35pm
 Education:
Ph.D.  University of California  Los Angeles  1996 
 Recent Publications
(More Publications)
 Zhao, H; Zhong, Y, Quantitative PAT with simplified P N approximation,
Inverse Problems, vol. 37 no. 5
(May, 2021) [doi] [abs]
 Xiang, R; Lai, R; Zhao, H, A Dual Iterative Refinement Method for Nonrigid Shape Matching,
Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition
(January, 2021),
pp. 1592515934, IEEE, ISBN 9781665445092 [doi] [abs]
 Zhong, Y; Zhao, H; Ren, K, Separability of the kernel function in an integral formulation for anisotropic radiative transfer equation,
Siam Journal on Mathematical Analysis, vol. 53 no. 5
(2021),
pp. 56135613, Society for Industrial and Applied Mathematics
 Zhao, H; Li, J, Scalable Incremental Nonconvex Optimization Approach for Phase Retrieval,
Journal of Scientific Computing
(2021), Springer (part of Springer Nature)
 Zhao, H; Bryson, J; Vershynin, R, MarchenkoPastur law with relaxed independence conditions,
Random Matrices: Theory and Applications
(2021), World Scientific Publishing [doi] [abs]
 Recent Grant Support
 Learning Partial Differential Equation (PDE) and Beyond, National Science Foundation, 2023/072026/06.
 RTG: Training Tomorrow's Workforce in Analysis and Applications, National Science Foundation, 2021/072026/06.
 Computational Forward and Inverse Radiative Transfer, National Science Foundation, 2020/072024/06.


dept@math.duke.edu
ph: 919.660.2800
fax: 919.660.2821
 
Mathematics Department
Duke University, Box 90320
Durham, NC 277080320

