Brief Biography

Biography

Zhang Jin, originally from Yuexi County, Anqing City, Anhui Province, is an Associate Professor in the Department of Mathematics at Southern University of Science and Technology (SUSTech) and the  Shenzhen  National  Applied  Mathematics  Center.  He obtained his bachelor's and master's degrees from Dalian University of Technology in 2007 and 2010, respectively, and completed his Ph.D. at the University of Victoria in Canada  in  2014. From 2015 to 2018, he worked in the Department of Mathematics at Hong Kong Baptist University before joining  SUSTech in early 2019.

Dr. Zhang's research focuses on optimization theory and applications. His significant achievements have been published in influential optimization, computational mathematics, and machine learning journals and conferences such as Math Program, SIAM J Optim, Math Oper Res, SIAM J  Numer  Anal, J Mach Learn Res,  IEEE Trans Pattern Anal Mach Intell, as well as ICML, NeurIPS, ICLR, and others.

He has received recognition for his research contributions, including the Youth Science and Technology Award from the Operations Research Society of China and the Youth Science and Technology  Innovation Award from Guangdong Province. He has led several research projects, including the National Natural Science  Foundation's Outstanding Youth Fund, the Tianyuan Key Program, the General Program, the Guangdong Provincial Natural Science Foundation's Distinguished Young Scholar Program, the Shenzhen Talent Program for Technological Innovation, and the Key Research  and Development Program of the Ministry of Science and Technology's Special Project on Mathematics and Applied Mathematics.

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, Southern University of Science and Technology.

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

2015/03 - 2019/01, Research assistant professor, Hong Kong Baptist University.

2023/02 - present, Associate vice director, National Center for Applied Mathematics Shenzhen 

2021/09 - 2023/01, Assistant to director, National Center for Applied Mathematics Shenzhen

Recruitment Notice

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: I am interested in students (with strong mathematics or computing background, not necessarily majored in optimization) who are willing to work hard on challenging problems in optimization. Salary package is competitive, about ￥110,000 per year. If interested, please send me an email to request for more details on our PhD programs.

Research

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, Journal of Industrial and Management Optimization.

Research Grants

Principal Investigator: The National Science Fund of China, Key Program Grant, "theory and method of foundation model reduction", 1,000,000 RMB, 2024 - 2025.(on-going)

Principal Investigator:  National Key Program of China, "Research on Deep Learning Models for Multi-Modal Image Data", 3,200,000 RMB, 2024 - 2028.(on-going)

Principal Investigator: National Natural Science Foundation of China, Excellent Young Investigator Grant, "Optimization theory and methods",2,000,000 RMB, 2023 - 2025. (on-going)

Principal Investigator: Guangdong  Basic and Applied Basic Research Foundation,  Distinguished Young Investigator Grant, “ Bilevel Programming: theory, method and application ”, 1,000,000 RMB, 2022 - 2025.(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 ”, 1,800,000 RMB, 2021 - 2024.

Principal Investigator: The Science and Technology Innovation Committee of Shenzhen Municipality, General fund, "Applications of Bi-level programming in contract theory ”, 500,000 RMB,2021 - 2023. (Finished)

Principal Investigator: National Natural Science Foundation of China General Grant,“ Study on linear convergence of some splitting methods via variational analysis ”,520,000 RMB, 2020 -2023. (Finished)

Principal Investigator: Principal Investigator: National Natural Science Foundation of China, Young Scholar Grant, “Study on large-scale bilevel programming: optimality and algorithm ”, 200,000 RMB, 2017 - 2019. (Finished)

Principal Investigator:Research Grants Council of Hong Kong, “ Linear   convergence    of the(randomized block coordinate) proximal gradient methods via variational analysis ”, 300,000 HK Dollars, 2018 - 2021. (terminated due to departure)

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

Teaching

Courses-taught

MATH3205: Linear and Integer Programming, Fall 2016, HKBU

MATH3427: Real Analysis, Fall 2016, HKBU

MATH1006: Advanced Calculus, Spring 2018, HKBU

MA210: Operations Research, Spring 2019/Spring 2020/Spring 2021/Spring 2022/Spring 2023,SUSTech

MA433: Optimization Theory and Method, Fall 2019/ Fall 2020, SUSTech

MA101B: Calculus, Fall 2020, SUSTech

MAT7083: Convex Optimization Algorithm, Fall 2021/ Fall 2022/ Fall 2023, SUSTech

Research Group

Research Assistant Professor:

Dr. Wei Yao (June 2022 - Present), Wuhan University (Bachelor's), The Chinese University of Hong Kong (Ph.D.), Southern University of Science and Technology (Postdoctoral Researcher)

Visiting Scholars

Associate Professor Miantao Chao (January 2022 - January 2023), Guangxi University

Professor Qingjie Hu (January 2022 - January 2023), Guilin University of Electronic Technology

Assistant  Professor  Kuang  Bai  (February  2022  -  August   2022),  The Hong Kong Polytechnic University

Associate Professor Jiangxing Zhu (January 2021 - January 2022), Yunnan University 

Associate Professor Peili Li (July 2023 - Present), Henan University

Postdoctoral Researchers

Dr. Yao Wei (April 2020 - May 2022), Wuhan University (Bachelor's), The Chinese University of Hong Kong (Ph.D.)

Dr.   Xuan   Luo   (August 2021 - Present),  Huazhong University of Science and Technology (Bachelor's), City University of Hong Kong (Ph.D.)

Dr. Chunhai Hu (June 2022 - Present), Yunnan University (Bachelor's/Ph.D.)

Dr. Weihao Mao (March 2023 - Present), Wuhan University of Technology (Bachelor's), Xiamen University (Ph.D.)

Dr.  Hai'an  Yin  (July  2023 - Present),  Southeast  University  (Bachelor's),  Southern  University  of Science and Technology (Master's/Ph.D.)

Ph.D. Students

Hai'an Yin (September 2019 - June 2023), Southeast University (Bachelor's), Southern University of Science and Technology (Master's). Excellent Ph.D. Thesis in the 2023 Graduation of Southern University  of  Science  and  Technology,  Invited   Report  of  the   First  "Young  OR  Talent"  by  the Operations Research Society of China. Currently a Postdoctoral Researcher at Shenzhen National Applied Mathematics Center.

Yixia Song (September 2021 - Present), Zhengzhou University (Bachelor's), Southern University of Science and Technology (Master's)

Peixuan  Yang   (September   2022 - Present),   Jilin University   (Bachelor's),   Nankai   University (Master's)

Xiaoning Bai (September 2023 - Present), Northeastern University (Bachelor's), Beijing Institute of Technology (Master's)

Lvgang Zhang (September 2024 - Present), Jilin University (Bachelor's), Direct Ph.D. program

Qichao Cao (September 2024 - Present), University of Electronic Science and Technology of China (Bachelor's/Master's)

Jointly Supervised Ph.D. Students:

Yaoshuai  Ma  (Supervisor: Professor Xiao Wang, Peng Cheng Laboratory, September 2022 - Present), Liaoning Normal University (Bachelor's), Guangxi University (Master's)

Yixuan  Zhang   (Supervisor: Professor Xiaojun Chen, The Hong Kong Polytechnic University, September 2022 - Present), Beijing Normal University (Bachelor's), Southern University of Science and Technology (Master's)

Shanshan  Li  (Supervisor: Professor Xiao  Wang, Peng Cheng Laboratory,  September  2023 - Present), University of Electronic Science and Technology of China (Master's)

Master's Students:

Yixia Song  (September  2018  - July 2021), Zhengzhou  University  (Bachelor's),  currently  a  Ph.D. student at Southern University of Science and Technology

Chengming Yu (September 2019 - June 2023), Dalian University of Technology (Bachelor's)

Yixuan  Zhang  (September  2020 - July 2022), Beijing Normal University  (Bachelor's),  Excellent Graduate of the Faculty of Science at Southern University of Science and Technology in 2022, Excellent Master's Thesis at Southern University of Science and Technology in 2022, currently a Ph.D. student at The Hong Kong Polytechnic University

Kaiqi Sun (September 2021 - Present), Xiangtan University (Bachelor's)

Feifan  Wang  (September  2022 -  Present),  Southern   University  of  Science  and  Technology (Bachelor's)

Cheng Chen (September 2022 - Present), Hangzhou Dianzi University (Bachelor's) 

Zhihao Zhang (September 2022 - Present), Jilin University (Bachelor's)

Visiting Ph.D. Students:

Zhenping Yang (January 2019 - July 2019), Shanghai University, currently Associate Professor at Jiaying University

Shangzhi Zeng (September 2019 - March 2020, July 2020 - September 2021), The  University of Hong Kong, currently a Postdoctoral Researcher at Victoria University (PIMS), collaborating with Professor Jane Ye

Yanyun  Ding  (June  2020 - June  2023),  Beijing  University  of  Technology,  currently  Lecturer  at Shenzhen Vocational and Technical College.

Xiaoxiao Ma (August 2020 - August 2021), Victoria University.

Tianshu Chu (March 2023 - present), Beijing University of Technology.

Published Works

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, 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, preprint 2024.

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

Z.S. Lu, S.Y. Mei and J. Zhang, Sequential minimax optimization methods for bilevel optimization with strongly convex lower-level objective function, preprint 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.

X.M. Yang, W. Yao, H.A. Yin, S.Z. Zeng and J. Zhang, Gradient-based Algorithms for Multi-Objective Bi-Level Optimization, preprint 2023.

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

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

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  Learning, IEEE 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. Zhou. Second-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 Convexity, International 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 2022.  Available  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 optimization, Mathematical Programming 2022. Available 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 Feasibility, IEEE 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 Beyond, NeurIPS 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 ADMM, IEEE Transactions on Image Processing 2021

R.Z. Ke and J. Zhang, On the First Order Approach for Bilevel Programming: Moral Hazard Case, Operations 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, 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. (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 paper, 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 set, SIAM 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)