Email 中文

Faculty > Professors > ZHANG Jin

ZHANG Jin

Assistant Professor  

0755-88015915 http://faculty.sustech.edu.cn/zhangj9/en/

  • Brief Biography
  • Research
  • Teaching
  • Published Works

Biography


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. After working in Hong Kong Baptist University for four years, he arrived at Southern University of Science and Technology as a tenure-track assistant professor in January 2019.


Education and Qualifications


2014/12: Ph.D. in Applied Mathematics, University of Victoria, Canada.

2010/07: M.Sc. in Operational Research, Dalian University of Technology, China.

2007/07: B.Art in Journalism, Dalian University of Technology, China.


Employment

2019/01 - present, Tenure-track assistant professor, Department of Mathematics, Southern University of Science and Technology.

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.



Recruitment Notice


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 zhangj9@sustech.edu.cn.


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. 


Research Areas


Optimization theories: nonsmooth analysis, variational analysis and perturbational analysis

Bilevel programming problem/Mathematical programs with equilibrium constraints and their applications in machine learning and economics

Convergence analysis of first order methods via variational analysis

Stochastic programming and robust optimization


Professional Activities

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.


Research Grants

Principal Investigator: Research Grants Council of Hong Kong, ``Linear convergence of the (randomized block coordinate) proximal gradient methods via variational analysis'', 2018 - 2021. 0.3 million. (terminated due to departure)


Principal Investigator: National Natural Science Foundation of China for young scholar, ``Study on large-scale bilevel programming: optimality and algorithm'', 2017 - 2019. 0.2 million. (Finished)


Principal Investigator:  National Natural Science Foundation of China, General fund, "Study on linear convergence of some splitting methods via variational analysis'', 2020 - 2023. 0.5 million. (on-going)


Principal Investigator:  The Science and Technology Innovation Committee of Shenzhen Municipality, General fund, "Applications of Bi-level programming in contract theory'', 2021 - 2023. 0.5 million. (on-going)


Principal Investigator:  The Science and Technology Innovation Committee of Shenzhen Municipality, Excellent Young Investigator Grant, "Bi-level modelling and algorithms for meta-learning and hyperparameter learning'', 2021 - 2023. 1.8 million. (on-going)


Research Awards


Junior Research Award from Operations Research Society of China (ORSC), 2020


Junior Research Award from Faculty of Science, SUSTech, 2020


Courses-taught:



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


MA210:  Operations Research, Spring 2020, Southern University of Science and Technology


MA433:  Optimization Theory and Method, Fall 2020, Southern University of Science and Technology


MA100:  Calculus, Fall 2020, Southern University of Science and Technology


MA210:  Operations Research, Spring 2021, Southern University of Science and Technology





Research Group:


Long-term Visitor:

Prof. Jiangxing Zhu (2021.1 - Present) , from Yunnan University

Postdoctorate Fellows:

Dr. Wei Yao(2020.3 - Present) ,  from Wuhan University (B.Sc), Chinese University of Hong Kong (M.Phi, Ph.D)

Ph.D Students:

Haian Yin(2019.9 - Present), from Southeast University (B.Sc), Southern University of Science and Technology  (M.Phi)

Yanfei Feng(2020.8 - Present), from Nankai University (B.Sc, M.Phi)

Master Students:

Yixia Song(2018.9 - Present)from Zhengzhou University  (B.Sc)

Yixuan Zhang(2020.9 -Present), from Beijing Normal University (B.Sc)

Visiting Students:

Zhenping Yang(2019.1 - 2019.7), from Shanghai Univeristy

Shangzhi Zeng(2019.9 - 2020.3, 2020.7-Present), from the University of Hong Kong

Yanyun Ding(2020.6 - Present), from Beijing University of Technology

Xiaoxiao Ma(2020.8 - Present), from University of Victoria


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, X. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, Bilevel Meta Optimization: A Unified Framework for Optimization-Derived Learning, preprint 2021. 

R.S. Liu, Y.H. Liu, S.Z. Zeng and J. Zhang, Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond, preprint 2021. 

J. Zhang and X.D. Zhu, Linear Convergence of Stochastic First-Order Algorithms under Bounded Metric Subregularity, preprint 2021. 

R.Z. Ke and J. Zhang, On the First Order Approach for Bilevel Programming: Moral Hazard Casepreprint 2021. (pdf)

Y.W. Li, G.H. Lin, J. Zhang and X.D. Zhu, A novel approach for bilevel programs based on Wolfe duality, preprint 2021.

J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Difference of convex algorithms for bilevel programs with applications in hyperparameter selection, preprint 2021. (pdf)

R.S. Liu, P. Mu, X.M. Yuan, S.Z. Zeng and J. Zhang, A Generic Descent Aggregation Framework for Gradient-based Bi-level Optimization, preprint 2021, extension of ICML2020. (pdf)

L. Wang, H. Yin, J. Zhang, Density-based Distance Preserving Graph for Graph-based Learning, preprint 2021.

B. Mordukhovich, X.M. Yuan, S.Z. Zeng and J. Zhang, A globally convergent proximal Newton-type method in nonsmooth convex optimizationpreprint 2020. (pdf)

R.Z. Ke, W. Yao, J.J. Ye and J. Zhang, Generic property of the partial calmness condition for bilevel programming problems, preprint 2020.

L Chen, Y.C. Liu, X.M. Yang and J. Zhang, Stochastic approximation methods for the two-stage stochastic linear complementarity problem, preprint 2020.

R.S. Liu, P. Mu and J. Zhang, Investigating Customization strategies and convergence behaviors of task-specific ADMMpreprint 2019.

R.S. Liu, L. Ma, X.M. Yuan, S.Z. Zeng and J. Zhang, Task-Oriented Convex Bilevel Optimization with Latent Feasibility, preprint 2019.

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,  Set-Valued and Variational Analysis 2021  (special issue dedicated to Tyrrell Rockafellar's 85th birthday), to appear

R.S. Liu, X. Liu, X.M. Yuan, S.Z. Zeng and J. Zhang, A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization International Conference on Machine Learning (ICML) 2021, to appear (pdf)

Y.C. Liu and J. Zhang, Confidence Regions of Stochastic Variational Inequalities: Error Bound Approach, Optimization, 2020, to appear. (pdf)

Y.C. Liu, X.M. Yuan and J. Zhang, Discrete Approximation Scheme in Distributionally Robust Optimization, Numerical Mathematics: Theory, Methods and Applications, 2020, to appear (pdf)

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, Set-Valued and Variational Analysis, 2020, to appear (pdf)

R.S. Liu, P. Mu, X.M. Yuan, S.Z. Zeng and J. Zhang,  A generic first-order algorithmic framework for bi-Level programming beyond lower-level singleton, International Conference on Machine Learning (ICML) 2020, (pdf, supplementary,slides)

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, International Journal of Production Research, 2020, to appear. (pdf)

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, Journal of Machine Learning Research 21, (2020) 1-75. (pdf)

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 setSIAM Journal on Optimization 29, no. 4 (2019) 2986–3011. (pdf)

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. (pdf)

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. (pdf)

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.(pdf)

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.(pdf)

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. (pdf)

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. (pdf)
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. (pdf)
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. (pdf)
J.J. Ye and J. Zhang, Enhanced Karush-Kuhn-Tucker condition and weaker constraint qualifications. Mathematical Programming, 139, no. 1-2 (2013), 353--381. (pdf)


Publications with mainland students supervised and co-supervised


R.S. Liu, J.X. Gao, J. Zhang, D.Y. Meng and Z.C. Lin, Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond, preprint 2021.

Z.P. Yang, J. Zhang, Y.L. Wang and G.H. Lin, Variance-Based Subgradient Extragradient Method for Stochastic Variational Inequality Problems, Journal of Scientific Computing, 2020, to appear

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

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.