See more at my personal webpage: https://www.math.fsu.edu/~whuang2/index.html
I am looking for graduate students, if you are interested, please contact me by email.
Wen Huang (黄文）
Personal Information
Professor
School of Mathematical Sciences
Xiamen University
TEL: 0592-2580070
Email: wen.huang at xmu dot edu dot cn
Education
2011.09-2014.05 Florida State University Ph.D. in Applied and Computational Mathematics
2008.08-2011.08 Florida State University M. S. in Applied and Computational Mathematics
2003.09-2007.07 University of Science and Techonology of China B. S. in Information and Scientific Computing
Experience
2020.11-Present Xiamen University (China) Professor
2018.09-2020.11 Xiamen University (China) Associate Professor
2016.07-2018.06 Rice University (USA) Pfeiffer Postdoctoral Instructor
2014.09-2016.06 Université catholique de Louvain (Belgium) Postdoctoral Fellow
2004.05-2014.08 Florida State University (USA) Postdoctoral Fellow
2007.07-2008.07 G-bits Network Technology Co., Ltd (China) Game Designer for Numerical System
Selected Publications
Wen Huang*, Ke Wei*. "Riemannian Proximal Gradient Methods", Mathematical Programming Series A, accepted.
Wen Huang*, Paul Hand, Reinhard Heckel, Vladislav Voroninski. "A Provably Convergent Scheme for Compressive Sensing under Random Generative Priors", Journal of Fourier Analysis and Applications, accepted.
Chafik Samir*, Wen Huang*. "Coordinate Descent Optimization for One-to-One Correspondence with Applications to Supervised Classification of 3D Shapes", Applied Mathematics and Computation, accepted.
Xinru Yuan, Wen Huang*, P.-A. Absil, K. A. Gallivan. "Computing the matrix geometric mean: Riemannian vs Euclidean conditioning, implementation techniques, and a Riemannian BFGS method", Numerical Linear Algebra with Applications, 27:5, 1-23, 2020.
Sean Martin, Andrew M. Raim, Wen Huang, Kofi P. Adragni*. "ManifoldOptim: An R Interface to the ROPTLIB Library for Riemannian Manifold Optimization", Journal of Statistical Software, 93:1, pp. 1-32, 2020.
Wen Huang*, Paul Hand. "Blind Deconvolution by a Steepest Descent Algorithm on a Quotient Manifold", SIAM Journal on Imaging Sciences, 11:4, pp. 2757-2785, 2018.
Wen Huang*, P.-A. Absil, Kyle Gallivan, Paul Hand. "ROPTLIB: an object-oriented C++ library for optimization on Riemannian manifolds", ACM Transactions on Mathematical Software, 44:4, pp. 43:1-43:21, 2018.
Somayeh Hosseini, Wen Huang*, Roholla Yousefpour. "Line Search Algorithms for Locally Lipschitz Functions on Riemannian Manifolds", SIAM Journal on Optimization, 28(1), pp. 596-619, 2018.
Wen Huang*, P.-A. Absil, Kyle Gallivan. "A Riemannian BFGS Method without Differentiated Retraction for Nonconvex Optimization Problems", SIAM Journal on Optimization, 28:1, pp. 470-495, 2018.
Wen Huang*, Kyle A. Gallivan, Xiangxiong Zhang. "Solving PhaseLift by low-rank Riemannian optimization methods for complex semidefinite constraints", SIAM Journal on Scientific Computing, 39:5, pp. B840-B859, 2017.
Jim Wilgenbusch*, Wen Huang, Kyle A. Gallivan. "Visualizing Phylogenetic Tree Landscapes", BMC Bioinformatics, 18:85, DOI:10.1186/s12859-017-1479-1, 2017.
Wen Huang*, P.-A. Absil, Kyle Gallivan. "Intrinsic Representation of Tangent Vectors and Vector Transport on Matrix Manifolds", Numerische Mathematik, 136:2, p.523-543, DOI:10.1007/s00211-016-0848-4, October, 2017.
Wen Huang*, Guifang Zhou, Melissa Merchand, Jeremy Ash, Paul Van Dooren, Jeremy M. Brown, Kyle A. Gallivan, Jim Wilgenbush. "TreeScaper: visualizing and extracting phylogenetic signal from sets of trees", Molecular Biology and Evolution, 33(12):3314-3316 DOI:10.1093/molbev/msw196, 2016.
Guifang Zhou, Wen Huang, Kyle Gallivan, Paul Van Dooren, P.-A. Absil*. "A Riemannian rank-adaptive method for low-rank optimization", Neurocomputing, 192, 72-80, June 2016.
Wen Huang*, Kyle A. Gallivan, Anuj Srivastava, Pierre-Antoine Absil. "Riemannian Optimization for Registration of Curves in Elastic Shape Analysis", Journal of Mathematical Imaging and Vision, 54(3), 320-343, 2016.
Wen Huang*, Kyle A. Gallivan, Pierre-Antoine Absil. "A Broyden Class of Quasi-Newton Methods for Riemannian Optimization", SIAM Journal on Optimization, 25:3, pp. 1660-1685, 2015.
Wen Huang, Pierre-Antoine Absil*, Kyle A. Gallivan. "A Riemannian symmetric rank-one trust-region method", Mathematical Programming Series A, 150:2, pp. 179-216, 2015.