Professor Dr. Ye Zhang
Vice dean of Faculty of Computational Mathematics and Cybernetics, Shenzhen MSU-BIT University.
Head of Professorship Inverse Problems at Shenzhen MSU-BIT University
Contact Information:
Postal address: Shenzhen MSU-BIT University, 1 International University Park Road, Longgang District, 518172 Shenzhen, Guangdong Province, P.R. China.
Office: Room 323, Main Building.
Phone: 28323171
Email: [email protected]
Recruiting: several Postdocs. Email me for details. 招聘北理博士（每年2名）和博后（若干，每年30萬+）。
Education
PhD in Mathematical Physics (01.01.03), Lomonosov Moscow State University, 2014.
Professional Appointments
?Aug. 2020 – present, Professor, School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, and Faculty of Computational Mathematics and Cybernetics, Shenzhen MSU-BIT University.
?Sep. 2019 – Aug. 2020, Associate Professor, School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, and Faculty of Computational Mathematics and Cybernetics, Shenzhen MSU-BIT University, Associate Professor, Shenzhen MSU-BIT University.
?Feb. 2018 – Sep. 2019, Humboldt Fellowship, Faculty of Mathematics, Chemnitz University of Technology, Germany.
?Dec. 2017 – Sep.2019, Researcher, Unit of Mathematics, School of Science and Technology, Orebro University, Sweden.
?Jul. 2016 – Nov. 2017, Researcher, Department of Chemistry and Biomedical Sciences, Karlstad University, Sweden.
?May 2014 – Jun. 2016, Postdoctoral Fellowship, Unit of Mathematics, School of Science and Technology, Orebro University,Sweden.
Awards and Honors
?Kovalevskaya grant for International Congress of Mathematicians 2022.
?High-level Overseas Talents: Youth Project, (National level, Central Organization Department), 2020.
?Excellent Instructor for Competition of Mathematical Modeling, Guangdong Province, 2020.
?Humboldt Research Fellowship for Postdoctoral Researchers, 2017.
?Chinese Government Award for Outstanding Self-Financed Students Abroad, 2012.
Editorial Board of Journals
? Journal of Inverse and Ill-posed Problems
? Communications on Analysis and Computation
Research Group
? Members: Associate Prof. Alexey Shcheglov, Senior Lecturer Chun Li, Lecturer Jianxun Yang, Lecturer Chao Wang.
? Postdocs: Dmitrii Chaikovskii, Haie Long, Yuping Li, Quan Mu.
? Doctoral Students: Qin Huang, Yingao Wang, You Sun, Lan Wang, Qiao Zhu, Zhiman Luan, Jiacheng Pan, Jing Li, Chenyu Zhang.
? Secretary: Limei Xu.
? Visiting Researcher: Lele Yuan.
Fundings
?06/2024 -- 06/2029, Shenzhen Science and Technology Program (Grant No. RCJC20231211090030059), Principal Investigator, (杰出青年, 4 million CNY)
?10/2022 -- 09/2025, National Key Research and Development Program of China (Grant No. 2022YFC3310300), Principal Investigator, (青年科學家項目, 3 million CNY)
?01/2022--12/2025, National Natural Science Foundation of China (NSFC) (Grant No. 12171036), Principal Investigator, (面上項目, 510,000 CNY).
? 08/2021--08/2025, Beijing Natural Science Foundation (Key project, No. Z210001), Principal Investigator, (重點項目, 2 million CNY)
? 01/2021--12/2022, Shenzhen Science and technology innovation Commission (Grant No. 20200827173701001), Principal Investigator, (穩定支持項目, 500,000 CNY).
? 01/2020--12/2022, Guangdong Basic and Applied Basic Research Foundation (Grant No. 2019A1515110971), Principal Investigator, (面上項目, 100,000 CNY).
Monographs:
1. Zhang Y. and Lukyanenko D.V., Methods for Numerical Diagnosis of Explosion Solutions in Mathematical Physics Equations, Science Press, 2022 March, ISBN: 978-7-03-071785-6, 131pp (in Chinese).
1. 張曄, D.V. 盧基揚年科, 數學物理方程爆破解的數值診斷方法. 科學出版社, 2022年3月.
2. Zhang Y. and Lukyanenko D.V., Parallel Computing, Science Press, 2024 December, ISBN: 978-7-03-077682-2, 238pp (in Chinese).
2. 張曄, D.V. 盧基揚年科, 并行計算. 科學出版社, 2024年12月.
Selected publications (*Corresponding author)
[57] Yuan L., Zhang Y., A Scaling Fractional Asymptotical Regularization Method for Linear Inverse Problems, Advances in Computational Mathematics, 2025, accepted.
[56] Long H., Zhang Y., Gao G., An accelerated inexact Newton regularization scheme with a learned feature-selection rule for non-linear inverse problems, Inverse Problems, 2024, 40(8), 085011.
[55] Liubavin A., Mingkang N., Zhang Y., Chaikovskii1 D., Asymptotic Solution for Three-Dimensional Reaction–Diffusion–Advection Equation with Periodic Boundary Conditions, Differential Equations, 2024, 60 (9), 1134–1152.
[54] Liu S., Luan Z., Kabanikhin S.I., Strijhak S.V., Zhang Y., Solving a type of nonlinear Schrodinger equations using a physically informed neural network and tuning the adaptive activation function, TWMS Journal of Pure and Applied Mathematics, 2024, 15(2), 203-227.
[53] Gong R., Liu X., Shen J., Huang Q., Sun C., Zhang Y., Uniqueness and numerical inversion in bioluminescence tomography with time-dependent boundary measurement, Inverse Problems, 2024, 40(7), 075002.
[52] Long H., Zhang Y., Gao G., An accelerated inexact Newton-regularizing algorithm for ill-posed operator equations, Journal of Computational and Applied Mathematics, 2024, 451, 116052.
[51] Xihang Qiu#, Lixian Zhu#, Zikai Song, Zeyu Chen, Haojie Zhang, Kun Qian*, Ye Zhang*, Bin Hu*, Yoshiharu Yamamoto, and Bj?rn W. Schuller, “Study Selectively: An Adaptive Knowledge Distillation based on a Voting Network for Heart Sound Classification”, in Proceedings of the INTERSPEECH, pp.1-5, Kos Island, Greece, September 2024.
[50] Chen D., Li J., Zhang Y.*, A posterior contraction for Bayesian inverse problems in Banach spaces, Inverse Problems, 2024, 40, 045011.
[49] Wang Y., Huang Q., Yao Z., Zhang Y.*, On a class of linear regression methods, Journal of Complexity, 2024, 82, 101826.
[48] Huang Q., Gong R., Zhang Y., A new second-order dynamical method for solving linear inverse problems in Hilbert spaces, Applied Mathematics and Computation, 2024, 473, 128642.
[47] Zhang Y., Chen C., Stochastic linear regularization methods: random discrepancy principle and applications, Inverse Problems, 2024, 40, 025007.
[46] K. Zhu, Z. Shen, M. Wang, L. Jiang, Y. Zhang, T. Yang, H. Zhang, M. Zhang. Visual Knowledge Domain of Artificial Intelligence in Computed Tomography: A Review Based on Bibliometric Analysis. Journal of Computer Assisted Tomography. 2024. 48(4), 652-662.
[45] Chaikovskii D., Zhang Y.*, Solving forward and inverse problems involving a nonlinear three-dimensional partial differential equation via asymptotic expansions. IMA Journal of Applied Mathematics, 2023, 88, 525-557.
[44] Chaikovskii D., Liubavin A., Zhang Y.*, Asymptotic expansion regularization for inverse source problems in two-dimensional singularly perturbed nonlinear parabolic PDEs. CSIAM Transactions on Applied Mathematics, 2023,4(4), 721-757.
[43] Huang Q., Gong R., Jin Q., Zhang Y., A Tikhonov regularization method for Cauchy problem based on a new relaxation model. Nonlinear Analysis: Real World Applications, 2023, 74, 103935.
[42] Ran Q., Cheng X., Gong R., Zhang Y., A dynamical method for optimal control of the obstacle problem. Journal of Inverse and Ill-Posed Problems, 2023; 31(4): 577–594.
[41] Su J., Yao Z., Li C., Zhang Y., A Statistical Approach of Estimating Adsorption Isotherm Parameters in Gradient Elution Preparative Liquid Chromatography. Annals of Applied Statistics, 2023, 17(4), 3476-3499.
[40] Shcheglov A., Li J., Wang C., Ilin A., Zhang Y., Reconstructing the Absorption Function in a Quasi-Linear Sorption Dynamic Model via an Iterative Regularizing Algorithm, Advances in Applied Mathematics and Mechanics, 2023, 16(1), 1-16.
[39] Gong R., Wang M., Huang Q., Zhang Y., A CCBM-based generalized GKB iterative regularization algorithm for inverse Cauchy problems. Journal of Computational and Applied Mathematics, 2023, 432(1), 115282.
[38] Chen D., Li J., Zhang Y., Convergence rates of stationary and non-stationary asymptotical regularization methods for statistical inverse problems in Banach spaces. Communications on Analysis and Computation, 2023, 1, 32-55.
[37] Zhang Y., On the acceleration of optimal regularization algorithms for linear ill-posed inverse problems. Calcolo, 2023, 60, 1, Article number: 6.
[36] Zhang Y., Chen C.. Stochastic asymptotical regularization for linear inverse problems. Inverse Problems, 2023, 39, 015007.
[35] Lysak T., Zakharova I., Kalinovich A., Zhang Y., Two-color self-similar laser beams in active periodic structures with Pt-symmetry and quadratic nonlinearity, AIP Conf. Proc., 2023, 2872, 060003.
[34] Abramyan M., Melnikov B., Zhang Y., Some more on restoring distance matrices between DNA chains: reliability coefficients. Cybernetics and Physics, 2023, 12(4), 237–251.
[33] Melnikov B., Zhang Y., Chaikovskii D.. An Algorithm for the Inverse Problem of Matrix Processing: DNA Chains, Their Distance Matrices and Reconstructing, Journal of Biosciences and Medicines, 2023, 11, 310-320.
[32] Chaikovskii D., Zhang Y.*. Convergence analysis for forward and inverse problems in singularly perturbed time-dependent reaction-advection-diffusion equations. Journal of Computational Physics, 2022, 470, 111609.
[31] Hu B., Qian K., Zhang Y., Shen J., Schuller B, The Inverse Problems for Computational Psychophysiology: Opinions and Insights. Cyborg and Bionic Systems, 2022, 2022, 9850248.
[30] Melnikov B., Zhang Y., Chaikovskii D., An inverse problem for matrix processing: an improved algorithm for restoring the distance matrix for DNA chains. Cybernetics and Physics, 2022, 11(4), 217–226.
[29] Yang J., Xu C., Zhang Y.. Reconstruction of the S-Wave Velocity via Mixture Density Networks With a New Rayleigh Wave Dispersion Function. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60, 035004.
[28] Xu C., Zhang Y.*. Estimating the memory parameter for potentially non-linear and non-Gaussian time series with wavelets. Inverse Problems, 2022, 38, 035004.
[27] Xu C., Zhang Y.*. Estimating adsorption isotherm parameters in chromatography via a virtual injection promoting double feed-forward neural network. Journal of Inverse and Ill-Posed Problems, 2022, 30(5), 693-712.
[26] Dong G. Hintermuller M, Zhang Y. A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging. SIAM Journal on Imaging Sciences, 2021, 14, 645-688.
[25] Zhang Y, Hofmann B. Two new non-negativity preserving iterative regularization methods for ill-posed inverse problems. Inverse Problems and Imaging, 2021, 15, 229-256.
[24] Zhang Y, Gong R. Second order asymptotical regularization methods for inverse problems in partial differential equations. Journal of Computational and Applied Mathematics, 2020, 375.
[23] Gong R, Hofmann B, Zhang Y*. A new class of accelerated regularization methods, with application to bioluminescence tomography. Inverse Problems, 2020, 36, 055013.
[22] Baravdish G, Svensson O, Gulliksson M, Zhang Y*. Damped second order flow applied to image denoising. IMA Journal of Applied Mathematics, 2019, 84, 1082–1111.
[21] Zhang Y, Yao Z, Forssen P, Fornstedt T. Estimating the rate constant from biosensor data via an adaptive variational Bayesian approach. Annals of Applied Statistics, 2019, 13, 2011-2042.
[20] Zhang Y, Hofmann B, On fractional asymptotical regularization of linear ill-posed problems in Hilbert spaces. Fractional Calculus and Applied Analysis, 2019, 22, 699-721.
[19] Zhang Y*, Hofmann B, On the second-order asymptotical regularization of linear ill-posed inverse problems. Applicable Analysis, 2020, 99, 1000–1025. (該雜志歷史最受歡迎文章之一、排名第一；高被引論文) https://www.tandfonline.com/doi/full/10.1080/00036811.2018.1517412
[18] Zhang Y*, Gong R, Gulliksson M, Cheng X. A coupled complex boundary expanding compacts method for inverse source problems. Journal of Inverse and Ill-Posed Problems, 2018, 27, 67-86.
[17] Zhang Y*, Gong R, Cheng X, Gulliksson M. A dynamical regularization algorithm for solving inverse source problems of elliptic partial differential equations. Inverse Problems, 2018, 34, 065001.
[16] Lin G, Cheng X, Zhang Y*. A parametric level set based collage method for an inverse problem in elliptic partial differential equations. Journal of Computational and Applied Mathematics, 2018, 340, 101-121.
[15] Zhang Y*, Forssen P, Fornstedt T, Gulliksson M, Dai X. An adaptive regularization algorithm for recovering the rate constant distribution from biosensor data. Inverse Problems in Science and Engineering, 2018, 26, 1464-1489.
[14] Dai X, Zhang C, Zhang Y, Gulliksson M. Topology optimization of steady Navier-Stokes flow via a piecewise constant level set method. Structural and Multidisciplinary Optimization. 2018, 57, 2193-2203.
[13] Yao Z, Zhang Y, Bai Z, Eddy W. Estimating the number of sources in magnetoencephalography using spiked population eigenvalues. Journal of the American Statistical Association, 2018, 113, 505-518.
[12] Cheng X, Lin G, Zhang Y, Gong R, Gulliksson M. A modified coupled complex boundary method for an inverse chromatography problem. Journal of Inverse and Ill-Posed Problems, 2018, 26, 33-49.
[11] Lin G, Zhang Y*, Cheng X, Gulliksson M, Forssen P, Fornstedt T. A regularizing Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem in chromatography. Applicable Analysis, 2018, 97, 13-40.
[10] Zhang Y*, Lin G, Gulliksson M, Forssen P, Fornstedt T, Cheng X. An adjoint method in inverse problems of chromatography. Inverse Problems in Science and Engineering, 2017, 25(8), 1112-1137.
[9] Zhang Y*, Lin G, Forssen P, Gulliksson M, Fornstedt T, Cheng X. A regularization method for the reconstruction of adsorption isotherms in liquid chromatography. Inverse Problems, 2016, 32(10), 105005.
[8] Gulliksson M, Holmbom A, Persson J, Zhang Y*. A separating oscillation method of recovering the G-limit in standard and non-standard homogenization problems. Inverse Problems, 2016, 32(2), 025005.
[7] Zhang Y*, Gulliksson M, Hernandez Bennetts V, Schaffernicht E. Reconstructing gas distribution maps via an adaptive sparse regularization algorithm. Inverse Problems in Science and Engineering, 2016, 24(7), 1186-1204.
[6] Zhang Y*, Lukyanenko D, Yagola A. Using Lagrange principle for solving two-dimensional integral equation with a positive kernel. Inverse Problems in Science and Engineering. 2016, 24(5), 811-831.
[5] Zhang Y*, Lukyanenko D, Yagola A. An optimal regularization method for convolution equations on the sourcewise represented set. Journal of Inverse and Ill-Posed Problems. 2016, 23(5), 465-475.
[4] Chen T, Gatchell M, Stockett M, Alexander J, Zhang Y, et al. Absolute fragmentation cross sections in atom-molecule collisions: scaling laws for non-statistical fragmentation of polycyclic aromatic hydrocarbon molecules. The Journal of Chemical Physics. 2014, 140(22) , 224-306.
[3] Zhang Y, Lukyanenko D, Yagola A. Using Lagrange principle for solving linear ill-posed problems with a priori information. Numerical Methods and Programming. 2013, 14, 468-482. (in Russian)
[2] Wang Y, Zhang Y*, Lukyanenko D, Yagola A. Recovering aerosol particle size distribution function on the set of bounded piecewise-convex functions. Inverse Problems in Science and Engineering, 2013, 21, 339-354.
[1] Wang Y, Zhang Y*, Lukyanenko D, Yagola A. A method of restoring the restoring aerosol particle size distribution function on the set of piecewise-convex functions. Numerical Methods and Programming, 2012, 13, 49-66. (in Russian)
Teaching
公共課：
本研究生
2021 Autumn: 機器學習/ Машинное обучение: алгоритмы и математическая теория (72課時), Building 2, Room 506.
本科
2021 Spring: 線性代數/ Линейная Алгебра (72課時), Building 1, Room 221.
數學建模：
2021 Winter School on Mathematical Modelling (25 Jan. 2021 -- 3 Feb. 2021, Tencent Meeting/613 3945 5524)
2020 Summer School on Mathematical Modelling (17 Aug. 2020 -- 5 Sep. 2020, Zoom Meeting/816 083 2954)
2020 Spring: 數學建模/ Математическое моделирование и исследование моделей с помощью математических программ (54課時)
Презентации:
