Faculty > Professors > ZHANG Jin

ZHANG Jin

Associate 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, and promoted to associate professor in November 2022. 


Editoral Service: Associate Editor of Numerical Algebra, Control and Optimization (NACO) 


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


2022/12 - present, Tenure-track associate professor, Department of Mathematics, Southern University of Science and Technology.


2019/01 - 2022/11, Tenure-track assistant professor, Department of Mathematics, Southern University of Science and Technology.

2015/04 - 2019/01, research assistant professor, Department of Mathematics, Hong Kong Baptist University.


Recruitment Notice: Ph.D student/Post-doc/RAP


Research assistant professor/Post-doc: Dr. Jin Zhang from Southern University of Science and Technology would like to hire RAP/postdoc. Ideal candidates should be familiar in optimization theory or application. Salary package is competitive and subject to research experience, basic package up to ¥500,000 per year for RAP and 350,000 per year for postdoc. If interested, please send your CV to zhangj9@sustech.edu.cn.


PhD Students in 2025: I am interested in students (not necessarily majored in optimization) who are willing to work hard on challenging problems in optimization. Salary package is competitive, about 110,000 per yearIf 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 optimization methods via variational analysis

Stochastic programming and robust optimization


Professional Activities

Guest editor for Pacific Journal of Optimization, special issue on hierarchical optimization.

Regular reviewer for major journals in optimization and operational research: Mathematical Programming, SIAM Journal on Optimization, Mathematics of Operations Research, 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.

Local organizing member for the Conference on Advances in Nonsmooth Analysis and Applications 2019, Southern University of Science and Technology.


Local organizing member for the Conference on Advances in Optimization Theory and Applications 2020, Southern University of Science and Technology.


Local organizing member for the Conference on Advances in Optimization Theory and Applications for Young Scholars 2021, Southern University of Science and Technology.


Organizing member for the Forum on Developments and Origins of Operations Research, Variational Analysis -- Theory and Application (online courses), 2021


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, Young scholar fund, ``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. (Finished)


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 - 2024. 1.8 million. (on-going)


Principal Investigator: Guangdong Basic and Applied Basic Research Foundation, Distinguished Young Investigator Grant, “Bilevel Programming: theory, method and application'', 2022 - 2025. 1 million. (on-going)


Principal Investigator: The National Science Fund of China, Excellent Young Investigator Grant“Optimization theory and method'', 2023 - 2025. 2 million. (on-going)


Principal Investigator: Natianal Key R&D Program of China, "Research on Deep Learning Models for Multi-Modal Image Data", 2024-2028, 3.2 million. (on-going) 


Research Awards

Junior Research Award from Department of Science and Technology of Guangdong Province, 2022

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 2019/2020/2021/2022/2023, Southern University of Science and Technology


MA433:  Optimization Theory and Method, Fall 2019/2020, Southern University of Science and Technology


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


MAT7083: Convex Optimization Algorithm, Fall 2021/2022/2023, Southern University of Science and Technology




Research Group:


Research Assistant Professor:

Dr. Wei Yao(2022.6 - Present), from Wuhan University (B.Sc), Chinese University of Hong Kong (M.Phi, Ph.D)


Long-term Visitor:

Prof. Jiangxing Zhu (2021.1 - 2022.1) , from Yunnan University

Prof Qingjie Hu (2022.1 - 2023.1) , from  Guilin University of Electronic Technology

Prof Miantao Chao (2022.1 - 2023.1) , from Guangxi University

Prof Peili Li (2023.7 - present), from Henan University


Postdoctorate Fellows:

Dr. Wei Yao(2020.3 - 2022.5) ,  from Wuhan University (B.Sc), Chinese University of Hong Kong (M.Phi, Ph.D)

Dr. Xuan Luo ( 2021.8 -  Present), from Huazhong University of Science and Technology (B.E), City University of Hong Kong (Ph.D)

Dr. Chunhai Hu(2022.6  Present), from Yunnan University  (B.Sc, Ph.D)

Dr. Weihao Mao(2023.3  Present), from Wuhan University of Technology (B.Sc), Xiamen University  (Ph.D)

Dr. Haian Yin(2023.7 - Present), from Southeast University (B.Sc), Southern University of Science and Technology  (M.Phi, Ph.D)


Ph.D Students:

Haian Yin(2019.9 - 2023.6), from Southeast University (B.Sc), Southern University of Science and Technology  (M.Phi)

Yixia Song(2021.9 - Present), from Zhengzhou University  (B.Sc), Southern University of Science and Technology  (M.Phi)

Peixuan Yang (2022.9 Present ), from Jilin University  (B.Sc), Nankai University (M.Phi)

Xiaoning Bai (2023.9 - Present ), from Northeastern University (B.Sc), Beijing Institute of Technology (M.Phi)


Co-Supervised Ph.D Students:

Yaoshuai Ma (Chief supervisor Prof. Xiao Wang from Pengcheng Lab, 2022.9 - Present), from Liaoning Normal University  (B.Sc), Guangxi University (M.Phi)

Yixuan Zhang (Chief supervisor Prof. Xiaojun Chen from Hong Kong Polytechnic University, 2022.9 - Present), from Beijing Normal University (B.Sc),Southern University of Science and Technology (M.Phi)


Master Students:

Yixia Song(2018.9 - 2021.7), from Zhengzhou University  (B.Sc), currently Ph.D student in Southern University of Science and Technology

Chengming Yu(2019.9 - 2023.6), from Dalian University of Technology (B.E)

Yixuan Zhang(2020.9 - 2022.7), from Beijing Normal University (B.Sc),currently Ph.D student in Hong Kong Polytechnic University superivsed by Prof Xiaojun Chen

Kaiqi Sun(2021.9 Present), from Xiangtan University (B.Sc)

Feifan Wang(2022.9 Present), from Southern University of Science and Technology (B.Sc)

Cheng Chen(2022.9 Present), from Hangzhou Dianzi University (B.Sc)

Zhihao Zhang (2022.9 - Present ), from Jilin University  (B.Sc)


Visiting Ph.D Students:

Zhenping Yang(2019.1 - 2019.7), from Shanghai Univeristy

Shangzhi Zeng(2019.9 - 2020.3, 2020.7-- 2021.9), from the University of Hong Kong. (Currently PIMS post-doc, University of Victoria, supervised by Prof Jane Ye)

Yanyun Ding(2020.6 - 2023.6), from Beijing University of Technology

Xiaoxiao Ma(2020.8 - 2021.8), from University of Victoria

Tianshu Chu(2023.3 - Present), from Beijing University of 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):


Y.S. Ma, X. Wang, W. Yao and J. Zhang, Beyond Convexity: Federated Bilevel Optimization Algorithms with Convergent Guarantees, preprint 2024.

W. Yao, H.A. Yin, S.Z. Zeng and J. Zhang, Overcoming Lower-Level Constraints in Bilevel Optimization: A Novel Approach with Regularized Gap Functions, preprint 2024.

L. Guo, H.A. Yin and J Zhang, A Penalized Sequential Convex Programming Approach for Continuous Network Design Problems, preprint 2024.

R.Z. Ke, C. Ryan, W. Yao and J. Zhang, A max-min reformulation approach to nonconvex bilevel optimizationpreprint 2023.

X.X. Ma, W. Yao, J.J. Ye and J. Zhang, Calm local optimality  for nonconvex-nonconcave minimax problems, preprint 2023.

L Gao, J.J. Ye, H.A. Yin, S.Z. Zeng and J. Zhang, Moreau Envelope Based Difference-of-weakly-Convex Reformulation and Algorithm for Bilevel Programs, preprint 2023.

R.S. Liu, Y.H. Liu, S.Z. Zeng and J. Zhang, Augmenting Iterative Trajectory for Bilevel Optimization: Methodology, Analysis and Extensions, preprint 2023.

M. Gao, W. Ouyang, J. Zhang and J.X. Zhu, Generalized metric subregularity for generalized subsmooth multifunctions in Asplund spacepreprint 2022. 

D. Wang, S.Z. Zeng and J. Zhang, A modularized algorithmic framework for interface related optimization problems using characteristic functions, preprint 2022.  

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




R.S. Liu, Z. Liu, W. Yao, S.Z. Zeng and J. Zhang, Moreau Envelope for Nonconvex Bi-Level Optimization: A Single-loop and Hessian-free Solution Strategy, International Conference on Machine Learning (ICML)  2024.

T.S. Chu, D.C. Xu, W. Yao and J. Zhang, SPABA: A Single-Loop and Probabilistic Stochastic Bilevel Algorithm Achieving Optimal Sample Complexity, International Conference on Machine Learning (ICML)  2024.

X.M. Yang, W. Yao, H.A. Yin, S.Z. Zeng and J. Zhang, Gradient-based Algorithms for Multi-Objective Bi-Level Optimization SCIENCE CHINA Mathematics 2024 (special issue on AI Methods for Optimization Problems)

W. Yao, C.M. Yu, S.Z. Zeng and J. Zhang, Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm, ICLR 2024 spotlight presentation (<5% out of 7262 submissions)

X.F. Wang, S.Z. Zeng, J. Zhang and J.C. Zhou, Proximal-based Methods can Guarantee Blunt Local Minimizer for Nonconvex Nonsmooth Optimization Problem, Operations Research Transactions 2023 (in Chinese) 

R.S. Liu, X. Liu, S.Z. Zeng, J. Zhang and Y.X. Zhang, Hierarchical Optimization-Derived LearningIEEE Transactions on Pattern Analysis and Machine Intelligence 2023

R.S. Liu, X. Liu, S.Z. Zeng, J. Zhang and Y.X. Zhang, Value-Function-based Sequential Minimization for Bi-level Optimization, IEEE Transactions on Pattern Analysis and Machine Intelligence 2023

K. Bai, Y.X. Song and J. Zhang, Second-order enhanced optimality conditions and constraint qualifications, Journal of Optimization Theory and Applications 2023

M. Benko, H. Gfrerer, J.J. Ye, J. Zhang and J.C. ZhouSecond-order optimality conditions for general nonconvex optimization problems and variational analysis of disjunctive systems, SIAM Journal on Optimization 2023

G.H. Lin, Z.P. Yang, H.A. Yin and J. Zhang, Dual-based stochastic inexact algorithm for a class of stochastic nonsmooth convex composite problems, Computational Optimization and Applications 2023.

R.S. Liu, X. Liu, W. Yao, S.Z. Zeng and J. Zhang, Averaged Method of Multipliers for Bi-Level Optimization without Lower-Level Strong ConvexityInternational Conference on Machine Learning (ICML) 2023.

L. Guo, J.J. Ye and J. Zhang, Sensitivity analysis of the maximal value function with applications in nonconvex minimax programs, Mathematics of Operations Research, 2023.  Available at arXiv:2303.01474

X.X. Ma, W. Yao, J.J. Ye and J. Zhang, Combined approach with second-order optimality conditions for bilevel programming problem, Journal of Convex Analysis 2023 (special issue in honor of Roger J-B Wets on his 85th birthday). Available at arXiv:2108.00179v2

J.J. Ye, X.M. Yuan, S.Z. Zeng and J. Zhang, Difference of convex algorithms for bilevel programs with applications in hyperparameter selection, Mathematical Programming 2022Available at arXiv (2102.09006).

L Chen, Y.C. Liu, X.M. Yang and J. Zhang, Stochastic approximation methods for the two-stage stochastic linear complementarity problem, SIAM Journal on Optimization, 2022

L Gao, J.J. Ye, H.A. Yin, S.Z. Zeng and J. Zhang. Value Function based Difference-of-Convex Algorithm for Bilevel Hyperparameter Selection Problems, International Conference on Machine Learning (ICML) 2022. Available at arXiv (2206.05976).

R.S. Liu, X. Liu, S.Z. Zeng, J. Zhang and Y.X. Zhang, Optimization-Derived Learning with Essential Convergence Analysis of Training and Hyper-training, International Conference on Machine Learning (ICML) 2022.  

B. Mordukhovich, X.M. Yuan, S.Z. Zeng and J. Zhang, A globally convergent proximal Newton-type method in nonsmooth convex optimizationMathematical Programming 2022Available at arXiv:2011.08166

R.S. Liu, P. Mu, X.M. Yuan, S.Z. Zeng and J. Zhang, A generic descent aggregation framework for gradient-based bilevel optimization, IEEE Transactions on Pattern Analysis and Machine Intelligence 2022. (pdf

R.S. Liu, L. Ma, X.M. Yuan, S.Z. Zeng and J. Zhang, Task-Oriented Convex Bilevel Optimization with Latent FeasibilityIEEE Transactions on Image Processing 2022.

J. Zhang and X.D. Zhu, Linear convergence of prox-SVRG method for separable nonsmooth convex optimization problems under bounded metric subregularity, Journal of Optimization Theory and Applications, 2022.

R.Z. Ke, W. Yao, J.J. Ye and J. Zhang, Generic property of the partial calmness condition for bilevel programming problems, SIAM Journal on Optimization, 2022 Available at arXiv (2107.14469).

R.S. Liu, Y.H. Liu, S.Z. Zeng and J. Zhang, Towards Gradient-based Bilevel Optimization with Non-convex Followers and BeyondNeurIPS Spotlight paper (< 3% out of 9122 submissions) 2021

L. Wang, H. Yin and J. Zhang, Density-based Distance Preserving Graph for Graph-based Learning, IEEE Transactions on Neural Networks and Learning Systems, 2021

R.S. Liu, P. Mu and J. Zhang, Investigating Customization strategies and convergence behaviors of task-specific ADMMIEEE Transactions on Image Processing 2021

R.Z. Ke and J. Zhang, On the First Order Approach for Bilevel Programming: Moral Hazard CaseOperations Research Transactions 2021 (in Chinese) (pdf)

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) (pdf)

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 (pdf)

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

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

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. (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. (75 pages long paperpdf)

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, IEEE Transactions on Pattern Analysis and Machine Intelligence 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, 2021

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. 

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.