Tenure-Track Assistant Professor
Carrying a dream to become a professional football journalist, Jin graduated with a B.A. in Journalism from Dalian University of Technology in 2007. As things didn't turn out as he wished, he chose to pursue a degree in mathematics. After completing a M.Sc. in operational research in Dalian University of Technology under the supervision of Professor Gui-Hua Lin, he moved to Canada in Oct. 2010. He earned a Ph.D. in applied mathematics from University of Victoria under the supervision of Professor Jane Juanjuan Ye in Dec. 2014.
Education and Qualifications
2015/07 - 2019/01, research assistant professor, Department of Mathematics, Hong Kong Baptist University.
2015/04 - 2015/06, research fellow, Department of Mathematics, Hong Kong Baptist University.
Post-doc: Dr. Jin Zhang from Southern University of Science and Technology would like to hire a postdoc. Ideal candidates should be familiar in optimization theory or application. Salary package is competitive and subject to research experience. If interested, please send your CV to email@example.com.
PhD Students: I am interested in students who are willing to work hard on challenging problems in optimization. If interested, please send me an email to request for more details on our PhD programs.
Jin Zhang's broad research area is comprised of optimization and variational analysis, as well as their applications in economics, engineering and data science.
Stochastic programming and robust optimization
Regular reviewer for major journals in optimization and operational research: Mathematical Programming, SIAM Journal on Optimization, European Journal of Operational Research, Annals of Operations Research, Operational Research Letters, Optimization Letters, Set-Valued and Variational Analysis, Pacific Journal of Optimization, Mathematical Methods of Operations Research.
Principal Investigator: Research Grants Council of Hong Kong, ``Linear convergence of the (randomized block coordinate) proximal gradient methods via variational analysis'', 2018 - 2021. withdrawn
Co-Principal Investigator: National Natural Science Foundation of China, ``Splitting method for large scale optimization problems and their applications'', 2019 - 2023. on-going
Principal Investigator: National Natural Science Foundation of China for young scholar, ``Study on large-scale bilevel programming: optimality and algorithm'', 2017 - 2019. on-going
Principal Investigator: National Natural Science Foundation of China general fund, "Study on linear convergence of some splitting methods via variational analysis'', 2020 - 2023. on-going
Principal Investigator: Natural Science Foundation of Guang Dong general fund, 2019 - 2022. on-going
MATH3205: Linear and Integer Programming, Fall 2016, Hong Kong Baptist University
MATH3427: Real Analysis, Fall 2016, Hong Kong Baptist University
MATH1006: Advanced Calculus, Spring 2018, Hong Kong Baptist University
MA210: Operations Research, Spring 2019, Southern University of Science and Technology
MA433: Optimization Theory and Method, Fall 2019, Southern University of Science and Technology
Selected publication（My co-authored works always list the authors in the alphabetical order of their names to indicate equal contributions, except the works in collaboration with mainland students due to their graduation requirements）：
R.S. Liu, P. Mu and J. Zhang, On the convergence of ADMM with task adaption and beyond, preprint 2019.
C. Fang, X.Y. Ma, J. Zhang and X.D. Zhu, Personality information sharing in supply chain systems for innovative products in the circular economy era, preprint 2019.
R.S. Liu, L. Ma, X.M. Yuan, S.Z. Zeng and J. Zhang, Bilevel integrative optimization for Ill-posed inverse problems, preprint 2019.
Y.C. Liu and J. Zhang, Confidence Regions of Stochastic Variational Inequalities: Error Bound Approach, preprint 2019.
X.M. Yuan, S.Z. Zeng and J. Zhang, Discerning the linear convergence of ADMM for structured convex optimization through the lens of variational analysis, preprint 2018.
J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Variational analysis perspective on linear convergence of some first order methods for nonsmooth convex optimization problems, preprint 2018.
Y.C. Liu, X.M. Yuan and J. Zhang, Discrete Approximation Scheme in Distributionally Robust Optimization, preprint 2018.
X.F. Wang, J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Perturbation techniques for convergence analysis of proximal gradient method and other first-order algorithms via variational analysis, preprint 2018.
J.S. Chen, J.J. Ye, J. Zhang and J.C. Zhou, Exact formula for the second-order tangent set of the second-order cone complementarity set, SIAM Journal on Optimization, to appear.
K. Bai, J.J. Ye and J. Zhang, Directional quasi/pseudo-normality as sufficient conditions for metric subregularity, SIAM Journal on Optimization 29, no. 4 (2019) 2625—2647
Y.C. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, Partial error bound conditions and the linear convergence rate of ADMM, SIAM Journal on Numerical Analysis 56, no. 4 (2018) 2095—2123
Y.C. Liu, H.F. Xu, S. Yang and J. Zhang, Distributionally robust equilibrium for continuous games: Nash and Stackelberg models, European Journal of Operational Research 265 no. 2 (2018) 631—643
Y.C. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, Primal-dual hybrid gradient method for distributionally robust optimization problem, Operational Research Letters 45 no. 6, (2017) 625—630
G.H. Lin, M.J. Luo, D.L. Zhang and J. Zhang, Stochastic second-order-cone complementarity problems: expected residual minimization formulation and its applications, Mathematical Programming, 165, no.1 (2017), 197-233.
G.H. Lin, M.J. Luo and J. Zhang, Smoothing and SAA method for stochastic programming problems with non-smooth objective and constraints. Journal of Global Optimization 66, no. 3 (2016), 487--510.
L. Guo, G.H. Lin, J.J. Ye and J. Zhang, Sensitivity analysis of the value function for parametric mathematical programs with equilibrium constraints. SIAM Journal on Optimization, 24, no. 3 (2014), 1206--1237.
J.J. Ye and J. Zhang, Enhanced Karush-Kuhn-Tucker conditions for mathematical programs with equilibrium constraints. Journal of Optimization Theory and Applications 163, no. 3 (2014), 777--794.
L. Guo, J.J. Ye and J. Zhang, Mathematical programs with geometric constraints in Banach spaces: enhanced optimality, exact penalty, and sensitivity. SIAM Journal on Optimization, 23, no. 4, (2013), 2295--2319.
J.J. Ye and J. Zhang, Enhanced Karush-Kuhn-Tucker condition and weaker constraint qualifications. Mathematical Programming, 139, no. 1-2 (2013), 353--381.
Publications with mainland students supervised and co-supervised
Z.P. Yang, J. Zhang, Y.L. Wang and G.H. Lin, Variance-Based Subgradient Extragradient Method for Stochastic Variational Inequality Problems, Preprint 2018
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, Some kind of Pareto stationarity for multiobjective problems with equilibrium constraints, Optimization, (2019) doi:10.1080/02331934.2019.1591406
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, New Constraint Qualifications for S-Stationarity for MPEC with Nonsmooth Objective, Asia Pacific Journal of Operational Research, (2019), DOI: 10.1142/S0217595919400013
X.D. Zhu, J. Zhang, J.C. Zhou and X.M. Yang, Mathematical programs with second-order cone complementarity constraints: strong stationarity and approximation method, Journal of Optimization Theory and Applications, (2019). doi.org/10.1007/s10957-018-01464-w
Z.P. Yang, J. Zhang, X.D. Zhu and G.H. Lin, SAA-based infeasible interior-point algorithms for a class of stochastic complementarity problems and their applications, Journal of Computational and Applied Mathematics, 352, (2019) 382—400
G. Sun, J. Zhang, L. Yu and G.H. Lin, A new complementarity function and applications in stochastic second-order cone complementarity problems, Journal of the Operations Research Society of China, (2018) doi.org/10.1007/s40305-018-0225-3
P. Zhang, J. Zhang, G.H. Lin and X.M. Yang, Constraint qualifications and proper Pareto optimality conditions for multiobjective problem with equilibrium constraints, Journal of Optimization Theory and Applications, 176 no. 3 (2018) 763—782
G.X. Wang, J. Zhang, B. Zeng and G.H. Lin, Expected residual minimization formulation for a class of stochastic linear second-order cone complementarity problems, European Journal of Operational Research 265 no. 2 (2018). 437—447
S.H. Jiang, J. Zhang, C.H. Chen and G.H. Lin, Smoothing partial exact penalty splitting method for mathematical programs with equilibrium constraints, Journal of Global Optimization, (2017). DOI: 10.1007/s10898-017-0539-4
Y. Zhao, J. Zhang, X.M. Yang and G.H. Lin, Expected residual minimization formulation for a class of stochastic vector variational inequalities. Journal of Optimization Theory and Applications 175 no. 2 (2017), 545--566.
M. Lei, J. Zhang, X. Dong and J.J. Ye, Modeling the bids of wind power producers in the day-ahead market with stochastic security-constrained market clearing, Sustainable Energy Technologies and Assessments. 16 (2016), 151--161.
L. Guo, J. Zhang and G.H. Lin, New results on constraint qualifications for nonlinear extremum problems and extensions. Journal of Optimization Theory and Applications 163, no. 3 (2014), 737--754.
Y.C. Liu, J. Zhang and G.H. Lin, Stochastic mathematical programs with hybrid equilibrium constraints. Journal of Computational and Applied Mathematics 235, no. 13 (2011), 3870--3882.