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: ye.zhang@smbu.edu.cn
Recruiting: several Postdocs. Email me for details. 招聘北理博士（每年2-4名）和博后（若干，每年30万+）。
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
► Applied Mathematics in Science and Engineering
► Communications on Analysis and Computation
Research Group
► Members: Associate Prof. Alexey Shcheglov, Senior Lecturers (Chun Li, Chao Wang, Dmitrii Chaikovskii, Haie Long, Yongming Lu), Lecturer (Jianxun Yang, Aleksei Liubavin)
► Current Postdocs: Yuping Li, Quan Mu, Deva Nithyanandham, Farwa Asmat.
► Current Doctoral Students: Yingao Wang, You Sun, Lan Wang, Qiao Zhu, Zhiman Luan, Jiacheng Pan, Jing Li, Chenyu Zhang, Yongbo Yu, Ruoli Wang, Kaiyu Lv.
► Former Postdocs: Dmitrii Chaikovskii (2020-2023), Haie Long (2021-2023)
► Former PhD: Qin Huang (2024)
► Secretary: Limei Xu.
► Visiting Researcher: Lele Yuan (2024-).
Fundings
►09/2025 -- 08/2028, National Key Research and Development Program of China (Grant No. 2025YFE0113400), Principal Investigator
►01/2025 -- 12/2026, National Natural Science Foundation of China (NSFC) (Grant No. W2421102), Principal Investigator
►06/2024 -- 06/2029, Shenzhen Science and Technology Program (Grant No. RCJC20231211090030059), Principal Investigator
►10/2022 -- 09/2025, National Key Research and Development Program of China (Grant No. 2022YFC3310300), Principal Investigator
►01/2022--12/2025, National Natural Science Foundation of China (NSFC) (Grant No. 12171036), Principal Investigator
► 08/2021--08/2025, Beijing Natural Science Foundation (Key project, No. Z210001), Principal Investigator
► 01/2021--12/2022, Shenzhen Science and technology innovation Commission (Grant No. 20200827173701001), Principal Investigator.
► 01/2020--12/2022, Guangdong Basic and Applied Basic Research Foundation (Grant No. 2019A1515110971), Principal Investigator
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. 张晔, D.V. 卢基扬年科, 数学物理方程爆破解的数值诊断方法. 科学出版社, 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. 张晔, D.V. 卢基扬年科, 并行计算. 科学出版社, 2024年12月.
Patents:
[1] 芦永明;张晔;雷涛;胡楠;张伟, 专利号：ZL 2024 1 1225144.7，一种基于各向异性介质初至波走时的射线路径追踪方法,授权公告日: 2024年11月22日.
[2] 程润泽;李春;周庆;程嘉荣;邱夕航;张晔;杨建勋;骆泳铭, 专利号：L 2025 1 0429723.1, 基于并行网络框架和动态融合的图像分割方法、系统、终端及存储介质,授权公告日: 2025年7月11日.
[3] 方宇浩;李春;周庆;程嘉荣;邱夕航;张晔;杨建勋, 专利号：ZL 2025 1 0445817.8, 基于混合网络框架的图像重建方法、系统、终端及存储介质,授权公告日: 2025年7月11日.
Computer Software Copyright:
[1] 深圳北理莫斯科大学, 一般微量物证液相色谱的计算软件V1.0.
Selected publications
2026
[92] Y. Sun, M. Cai, N. Yi, Y. Zhang, A concentration-preserving discontinuous Galerkin method for multi-component preparative chromatography, BIT Numerical Mathematics, 2026, 66 (3), 47.
[91] D. Nithyanandham, F. Augustin, Y. Zhang, S. Ramasamy, A bipolar fuzzy digraph-based integrated decision making model for sustainable underwater robot selection, Engineering Applications of Artificial Intelligence, 2026, 178, 115045.
[90] Y. Sun, S.I. Kabanikhin, C. Xu, Y. Zhang, Enhancing chromatographic resolution via smoothing-based global optimization and neural surrogate PDE modeling, Journal of Inverse and Ill-Posed Problems, 2026, 34(4):483-512.
[89] Q. Mu, Y. Zhang, Single scattering properties for an ensemble of randomly oriented convex polyhedra in the geometrical optics regime, Applied Optics, 2026, 65 (22), 7635-7644.
[88] C. Wang, N. Bondarenko, Y. Zhang, A regularization algorithm for inverse Sturm-Liouville problem on the star-shaped graph, Journal of Inverse and Ill-Posed Problems, 2026.
[87] S. Kabanikhin, M. Shishlenin, G. Bakanov, S. Liu, L. Yuan, Y. Zhang, Continuation problems: Theory, numerics, neural networks and applications, Journal of Inverse and Ill-Posed Problems, 2026, 34 (3), 455-479.
[86] R. Cheng, X. Qiu, M. Li, Y. Zhang, F.R. Yu, C. Li, Robust brain tumor segmentation with incomplete MRI modalities using Hölder divergence and mutual information-enhanced knowledge transfer, IEEE/CAA Journal of Automatica Sinica, 2026, 13 (4), 939-954.
[85] T. Jia, H. Zhang, H. Wu, Q. Sun, X. Jing, B. Meng, L. Shen, L. Wang, K. Qian, Y. Zhang, B. Hu, T. Schultz, B.W. Schuller, Y. Yamamoto, Breaking through data scarcity: A novel diffusion model approach for snoring sound augmentation and classification, Biomedical Signal Processing and Control, 2026, 116, 109449.
[84] W. Zhang, Y. Fang, X. Qiu, J. Cheng, J. Hong, B. Zhai, Q. Zhou, Y. Lu, Y. Zhang, C. Li, Proper Hölder-Kullback dirichlet diffusion: A framework for high dimensional generative modeling, Advances in Neural Information Processing Systems (NeurIPS), 2026, 38, 168693-168733.
[83] X. Qiu, J. Cheng, Y. Fang, W. Zhang, Y. Lu, Y. Zhang, C. Li, Federated dialogue-semantic diffusion for emotion recognition under incomplete modalities, Advances in Neural Information Processing Systems (NeurIPS), 2026, 38, 86146-86175.
[82] Q. Mu, Y. Zhang, Light scattering by a random convex polyhedron in the geometric optics approximation, Applied Optics, 2026, 65 (8), 2754-2762.
[81] J. Li, P. Yun, Y. Xu, Y. Zhang, M. Sun, Q. Chen, A. Ilin, R. Fan, HAPNet: Toward superior RGB-thermal scene parsing via hybrid, asymmetric, and progressive heterogeneous feature fusion, Biomimetic Intelligence and Robotics, 2026, 100309.
[80] C. V. Kumar, D. Nithyanandham, F. Augustin, S. Ramasamy, Y. Zhang, Adaptive low light image enhancement using bipolar fuzzy set, IEEE Transactions on Fuzzy Systems, 2026.
[79] C. Huang, J. Zhang, Y. Zhang, H. Wu, P. Cao, Z. Wang, Y. Yu, X. Cao, Latent fingerprint quality assessment for criminal investigations: A benchmark dataset and method, IEEE Transactions on Image Processing, 2026.
[78] L. Wang, H. Liang, Y. Zhang, A variable Lavrent'ev regularized collocation method for auto-convolution Volterra integral equations of the first kind, Journal of Scientific Computing, 2026, 106 (2), 38.
[77] Z. Luan, C. Yin, S. Norris, Y. Zhang, Stability analysis of Poiseuille-Rayleigh-Bénard convection of Jeffreys fluids in an inclined fluid-porous system, International Journal of Heat and Fluid Flow, 2026, 110273.
[76] CW J. Yang, Y. Zhang, S.I. Kabanikhin, C. Li, The level set approach for investigating Navier-Stokes flow in image reconstruction, TWMS Journal of Pure and Applied Mathematics, 2026, 17 (1), 149-166.
[75] Y. Zhang, Q. Zhu, R. Zhou, T. Lysak, C. Wang, Multi-layer 5D optical data storage: mathematical modeling and deep learning-based reconstruction of birefringent parameters, Computational Mathematics and Mathematical Physics, 2026, 66 (1), 120-135.
2025
[74] Z. Luan, C. Yin, S. Norris, Y. Zhang, Double-diffusive convection in two-layer viscoelastic fluid systems, 13th Australasian Natural Convection Workshop (13ANCW), 2025.
[73] D. Nithyanandham, F. Augustin, Y. Zhang, S. Ramasamy, A bipolar fuzzy integrated decision making model for underwater robot selection, 12th International Conference on Soft Computing & Machine Intelligence(ISCMI), 2025.
[72] Y. Fang, Z. Wang, Y. Lu, Y. Zhang, C. Li, A DeepONet-neural tangent kernel hybrid framework for physics-informed inverse source problems and robust image reconstruction, China Automation Congress (CAC), 2025.
[71] Y. Lu, Y. Zhang, T. Lei, N. Hu, Y. Tang, J. Zhang, An efficient method for calculating raypaths of first-arrival traveltimes in transversely isotropic media, Geophysical Prospecting, 2025, 73 (8), e70087.
[70] Z. Deng, Q. Zhou, Y. Fang, Z. Wang, Y. Lu, Y. Zhang, C. Li, Diffusion-low-rank hybrid reconstruction for sparse-view medical imaging, China Automation Congress (CAC), 2025, 4803-4808.
[69] Y. Zhang, M. Li, C. Li, Z. Liu, Y. Zhang, F. Yu, Uncertainty quantification via Hölder divergence for multi-view representation learning, IEEE Transactions on Multimedia, 2025.
[68] Y. Lu, W. Zhang, Y. Zhang, J. Yang, Traveltime calculations for qP, qSV, and qSH waves in tilted transversely isotropic media using a fast sweeping method with a Newton iterative solver, Geophysics, 2025, 90 (4), T109-T125.
[67] H. Long, Y. Zhang, Stochastic asymptotical regularization for nonlinear ill-posed problems, Inverse Problems, 2025, 41 (6), 065017.
[66] E. Junwu, M.J. Lee, Q. Deng, G. Tang, Z. Song, Y. Xu, Y. Zhang, A. Ilin, R. Fan, Transformer and trainable bilateral filter for unsupervised stereo matching, IEEE International Conference on Real-Time Computing and Robotics (RCAR), 2025.
[65] J. Wang, Z. Long, M.J. Lee, Y. Feng, Y. Xu, Y. Zhang, A. Ilin, X. Tang, R. Fan, Edge-aware and deformable feature fusion for steel surface defect segmentation, IEEE International Conference on Real-Time Computing and Robotics (RCAR), 2025.
[64] X. Qiu, W. Qiu, Y. Zhang, K. Qian, C. Li, B. Hu, B.W. Schuller, Y. Yamamoto, Fedkdc: Consensus-driven knowledge distillation for personalized federated learning in eeg-based emotion recognition, IEEE Journal of Biomedical and Health Informatics, 2025, 29 (8), 5527-5540.
[63] S. Liu, S. Kabanikhin, S. Strijhak, Y.A. Wang, Y. Zhang, Revisiting linear machine learning through the perspective of inverse problems, Journal of Inverse and Ill-Posed Problems, 2025, 33 (2), 281-303.
[62] L. Yuan, Y. Zhang, A scaling fractional asymptotical regularization method for linear inverse problems, Advances in Computational Mathematics, 2025, 51 (1), 8.
[61] H. Long, Y. Zhang, G. Gao, An accelerated inexact Newton-type regularizing algorithm for ill-posed operator equations, Journal of Computational and Applied Mathematics, 2025, 451, 116052.
2024
[60] R. Cheng, Z. Sun, Y. Zhang, C. Li, Robust divergence learning for missing-modality segmentation, China Automation Congress (CAC), 2024, 2077-2083.
[59] A. Liubavin, M. Ni, Y. Zhang, D. Chaikovskii, Asymptotic solution for three-dimensional reaction-diffusion-advection equation with periodic boundary conditions, Differential Equations, 2024, 60 (9), 1134-1152.
[58] H. Long, Y. Zhang, G. Gao, An accelerated inexact Newton regularization scheme with a learned feature-selection rule for non-linear inverse problems, Inverse Problems, 2024, 40 (8), 085011.
[57] Q. Huang, R. Gong, Y. Zhang, A new second-order dynamical method for solving linear inverse problems in Hilbert spaces, Applied Mathematics and Computation, 2024, 473, 128642.
[56] R. Gong, X. Liu, J. Shen, Q. Huang, C. Sun, Y. Zhang, Uniqueness and numerical inversion in bioluminescence tomography with time-dependent boundary measurement, Inverse Problems, 2024, 40 (7), 075002.
[55] 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.
[54] Y.A. Wang, Q. Huang, Z. Yao, Y. Zhang, On a class of linear regression methods, Journal of Complexity, 2024, 82, 101826.
[53] D.H. Chen, J. Li, Y. Zhang, A posterior contraction for Bayesian inverse problems in Banach spaces, Inverse Problems, 2024, 40 (4), 045011.
[52] Y. Zhang, C. Chen, Stochastic linear regularization methods: random discrepancy principle and applications, Inverse Problems, 2024, 40 (2), 025007.
[51] X. Qiu, L. Zhu, Z. Song, Z. Chen, H. Zhang, K. Qian, Y. Zhang, B. Hu, Y. Yamamoto, B.W. Schuller, Study selectively: An adaptive knowledge distillation based on a voting network for heart sound classification, Proc. Interspeech 2024, 2024, 137-141.
[50] A. Shcheglov, J. Li, C. Wang, A. Ilin, Y. Zhang, Reconstructing the absorption function in a quasi-linear sorption dynamic model via an iterative regularizing algorithm, Advances in Applied Mathematics and Mechanics, 2024, 16 (1), 237-252.
2023
[49] Q. Huang, R. Gong, Q. Jin, Y. Zhang, A Tikhonov regularization method for Cauchy problem based on a new relaxation model, Nonlinear Analysis: Real World Applications, 2023, 74, 103935.
[48] J. Su, Z. Yao, C. Li, Y. Zhang, A statistical approach to estimating adsorption-isotherm parameters in gradient-elution preparative liquid chromatography, The Annals of Applied Statistics, 2023, 17 (4), 3476-3499.
[47] R. Gong, M. Wang, Q. Huang, Y. Zhang, A CCBM-based generalized GKB iterative regularization algorithm for inverse Cauchy problems, Journal of Computational and Applied Mathematics, 2023, 432, 115282.
[46] T.M. Lysak, I.G. Zakharova, A.A. Kalinovich, Y. Zhang, Two-color self-similar laser beams in active periodic structures with PT-symmetry and quadratic nonlinearity, AIP Conference Proceedings, 2023, 2872 (1), 060003.
[45] D. Chaikovskii, Y. Zhang, Solving forward and inverse problems involving a nonlinear three-dimensional partial differential equation via asymptotic expansions, IMA Journal of Applied Mathematics, 2023, 88 (4), 525-557.
[44] Q. Ran, X. Cheng, R. Gong, Y. Zhang, A dynamical method for optimal control of the obstacle problem, Journal of Inverse and Ill-Posed Problems, 2023, 31 (4), 577-594.
[43] B.F. Melnikov, Y. Zhang, D. Chaikovskii, An algorithm for the inverse problem of matrix processing: DNA chains, their distance matrices and reconstructing, Journal of Biosciences and Medicines, 2023, 11 (5), 310-320.
[42] D.H. Chen, J. Li, Y. Zhang, Convergence rates of stationary and non-stationary asymptotical regularization methods for statistical inverse problems in Banach spaces, Commun. Anal. Comput., 2023, 1 (1), 32-55.
[41] Y. Zhang, On the acceleration of optimal regularization algorithms for linear ill-posed inverse problems, Calcolo, 2023, 60 (1), 6.
[40] M. Abramyan, B. Melnikov, Y. Zhang, Some more on restoring distance matrices between DNA chains: reliability coefficients, Cybernetics and Physics, 2023, 12 (4), 237-251.
[39] Y. Zhang, C. Chen, Stochastic asymptotical regularization for linear inverse problems, Inverse Problems, 2023, 39 (1), 015007.
[38] D. Chaikovskii, A. Liubavin, Y. Zhang, 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.
2022
[37] D. Chaikovskii, Y. Zhang, Convergence analysis for forward and inverse problems in singularly perturbed time-dependent reaction-advection-diffusion equations, Journal of Computational Physics, 2022, 470, 111609.
[36] C. Xu, Y. Zhang, 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.
[35] B. Hu, K. Qian, Y. Zhang, J. Shen, B.W. Schuller, The inverse problems for computational psychophysiology: Opinions and insights, Cyborg and Bionic Systems, 2022.
[34] J. Yang, C. Xu, Y. Zhang, 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, 1-13.
[33] C. Xu, Y. Zhang, Estimating the memory parameter for potentially non-linear and non-Gaussian time series with wavelets, Inverse Problems, 2022, 38 (3), 035004.
[32] B. Melnikov, Y. Zhang, D. Chaikovskii, 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.
2021
[31] G. Dong, M. Hintermueller, Y. Zhang, A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging, SIAM Journal on Imaging Sciences, 2021, 14 (2), 645-688.
[30] Y. Zhang, B. Hofmann, Two new non-negativity preserving iterative regularization methods for ill-posed inverse problems, Inverse Problems and Imaging, 2021, 15(2), 229-256.
2020
[29] R. Gong, B. Hofmann, Y. Zhang, A new class of accelerated regularization methods, with application to bioluminescence tomography, Inverse Problems, 2020, 36 (5), 055013.
[28]Y. Zhang, B. Hofmann, On the second order asymptotical regularization of linear ill-posed inverse problems, Applicable Analysis, 2020, 99, 1000–1025.
2019
[27] G. Baravdish, O. Svensson, M. Gulliksson, Y. Zhang, Damped second order flow applied to image denoising, IMA Journal of Applied Mathematics, 2019, 84 (6), 1082-1111.
[26] Y. Zhang, Z. Yao, P. Forssen, T. Fornstedt, Estimating the rate constant from biosensor data via an adaptive variational Bayesian approach, Annals of Applied Statistics, 2019, 13(4), 2011-2042.
[25] Y. Zhang, B. Hofmann, On fractional asymptotical regularization of linear ill-posed problems in Hilbert spaces, Fractional Calculus and Applied Analysis, 2019, 22 (3), 699-721.
[24] G. Dong, M. Hintermueller, Y. Zhang, A class of second-order geometric quasilinear hyperbolic PDEs and their application in imaging science, 2019, 14(2), 645-688.
[23] Y. Zhang, M. Gulliksson, M. Ögren, A. Oleynik, Damped dynamical systems for solving equations and optimization problems, Handbook of the Mathematics of the Arts and Sciences, 2019, 2171-2215.
2018
[22] Y. Zhang, P. Forssén, T. Fornstedt, M. Gulliksson, X. Dai, An adaptive regularization algorithm for recovering the rate constant distribution from biosensor data, Inverse Problems in Science and Engineering, 2018, 26 (10), 1464-1489.
[21] G. Lin, X. Cheng, Y. Zhang, 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.
[20] X. Cheng, Y. Zhang, R. Gong, M. Gulliksson, A coupled complex boundary expanding compacts method for inverse source problems, Journal of Inverse and Ill-Posed Problems, 2018, 27(1), 67-86.
[19] Y. Zhang, R. Gong, Second order asymptotical regularization methods for inverse problems in partial differential equations, Journal of Computational and Applied Mathematics, 2018, 375:112798.
[18] Y. Zhang, R. Gong, X. Cheng, M. Gulliksson, A dynamical regularization algorithm for solving inverse source problems of elliptic partial differential equations, Inverse Problems, 2018, 34 (6), 065001.
[17] X. Dai, C. Zhang, Y. Zhang, M. Gulliksson, Topology optimization of steady Navier-Stokes flow via a piecewise constant level set method, Structural and Multidisciplinary Optimization, 2018, 57 (6), 2193-2203.
[16] Z. Yao, Y. Zhang, Z. Bai, W.F. Eddy, Estimating the number of sources in magnetoencephalography using spiked population eigenvalues, Journal of the American Statistical Association, 2018, 113 (522), 505-518.
[15] X. Cheng, G. Lin, Y. Zhang, R. Gong, M. Gulliksson, A modified coupled complex boundary method for an inverse chromatography problem, Journal of Inverse and Ill-Posed Problems, 2018, 26 (1), 33-49.
[14] G. Lin, Y. Zhang, X. Cheng, M. Gulliksson, P. Forssén, T. Fornstedt, A regularizing Kohn-Vogelius formulation for the model-free adsorption isotherm estimation problem in chromatography, Applicable Analysis, 2018, 97 (1), 13-40.
2017
[13] Y. Zhang, G. Lin, M. Gulliksson, P. Forssén, T. Fornstedt, X. Cheng, An adjoint method in inverse problems of chromatography, Inverse Problems in Science and Engineering, 2017, 25 (8), 1112-1137.
[12] L. Flodén, A. Holmbom, P. Jonasson, T. Lobkova, M.O. Lindberg, Y. Zhang, A discussion of a homogenization procedure for a degenerate linear hyperbolic-parabolic problem, AIP Conference Proceedings, 2017, 1798 (1), 020177.
2016
[11] Y. Zhang, G.L. Lin, P. Forssén, M. Gulliksson, T. Fornstedt, X.L. Cheng, A regularization method for the reconstruction of adsorption isotherms in liquid chromatography, Inverse Problems, 2016, 32 (10), 105005.
[10] Y. Zhang, M. Gulliksson, V. M. Hernandez Bennetts, E. Schaffernicht, Reconstructing gas distribution maps via an adaptive sparse regularization algorithm, Inverse Problems in Science and Engineering, 2016, 24 (7), 1186-1204.
[9] Y. Zhang, D.V. Lukyanenko, A.G. Yagola, Using Lagrange principle for solving two-dimensional integral equation with a positive kernel, Inverse Problems in Science and Engineering, 2016, 24 (5), 811-831.
[8] M. Gulliksson, A. Holmbom, J. Persson, Y. Zhang, A separating oscillation method of recovering the G-limit in standard and non-standard homogenization problems, Inverse Problems, 2016, 32 (2), 025005.
2015
[7] Y. Zhang, D.V. Lukyanenko, A.G. Yagola, An optimal regularization method for convolution equations on the sourcewise represented set, Journal of Inverse and Ill-Posed Problems, 2015, 23 (5), 465-475.
2014
[6] T. Chen, M. Gatchell, M.H. Stockett, J.D. Alexander, Y. Zhang, P. Rousseau, A. Domaracka, S. Maclot, R. Delaunay, L. Adoui, B.A. Huber, T. Schlathölter, H.T. Schmidt, H. Cederquist, H. Zettergren, 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).
2013
[5] Y. Zhang, D.V. Lukyanenko, A.G. Yagola, Применение принципа Лагранжа для решения линейных некорректно поставленных обратных задач с использованием априорной информации о решении, Вычислительные Методы и Программирование, 2013, 14, 468-482.
[4] A.G. Yagola, Y. Zhang, D.V. Lukyanenko, A method for solving one dimensional fredholm integral equation of the first kind on the set of bounded piecewise-convex functions, Методы Создания, Исследования и Идентификации Математических Моделей, 2013, 103.
[3] Y.F. Wang, Y. Zhang, D.V. Lukyanenko, A.G. Yagola, Recovering aerosol particle size distribution function on the set of bounded piecewise-convex functions, Inverse Problems in Science and Engineering, 2013, 21 (2), 339-354.
[2] Y. Zhang, D.V. Lukyanenko, A.G. Yagola, Using Lagrange principle for solving linear ill-posed problems with a priori information, Numerical Methods and Programming, 2013, 14 (4), 468-482.
2012
[1] Y. Wang, Y. Zhang, D.V. Lukyanenko, A.G. Yagola, A method of restoring the aerosol particle size distribution function on the set of piecewise-convex functions, Numerical Methods and Programming, 2012, 13 (1), 49-66.
Teaching
公共课：
本研究生
2021 Autumn: 机器学习/ Машинное обучение: алгоритмы и математическая теория (72课时), Building 2, Room 506.
本科
2021 Spring: 线性代数/ Линейная Алгебра (72课时), Building 1, Room 221.
数学建模：
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: 数学建模/ Математическое моделирование и исследование моделей с помощью математических программ (54课时)
Презентации:
