简历

教育背景

2014 年，加拿大维多利亚大学 ，数学与统计系 ，获 应用数学 哲学博士学位

Ph.D Thesis: Enhanced Optimality Conditions and New Constraint Qualifications for Nonsmooth Optimization Problems

Supervisor: Professor Jane Juanjuan Ye

2010 年，大连理工大学，数学科学学院，获 应用数学 理学硕士学位

Supervisor: 林贵华 教授

2007 年，大连理工大学，人文社会科学学院，获 新闻学 文学学士学位

工作经历

2022 年12月至今，南方科技大学，数学系，Tenure-track 副教授

2019 年1月至 2022 年11月，南方科技大学，数学系，Tenure-track  助理教授

2015 年4月至 2019 年1月，香港浸会大学，数学系，研究助理教授

2023年2月至今，深圳国家应用数学中心，副主任

2021年9月至 2023年1月，深圳国家应用数学中心 ，主任助理

科研

研究领域

最优化理论：变分分析，非光滑分析 ，扰动分析

双层规划 （均衡约束数学规划）理论、算法及在机器学习、理论经济学中应用

误差界条件及一阶优化算法线性收敛率分析

随机规划 / 鲁棒优化

基金项目

主持：国家自然科学基金 数学天元重点项目, "大模型约化的数学理论与方法", 2024-2025 ，100 万（在研）

主持：科技部重点研发计划项目课题，“面向多模影像数据的深度学习模型研究” ，2024-2028 ，320 万（在研）

参与：国家自然科学基金 重点项目, "基于多智能体协同学习的屏幕混合内容编码理论与方法", 2024-2028（在研）

主持：国家自然科学基金 优青项目, ”最优化理论与方法“, 2023-2025, 200 万（在研）

主持：广东省自然科学基金 杰青项目, ”双层规划理论、方法与应用“, 2022-2025, 100 万（在研）

主持：深圳市优秀科技创新人才培养 优青项目, ‘’元学习和超参数学习驱动的双层规划模型与算法‘’, 2021-2024. 180 万 (在研)

主持：深圳市高等院校稳定支持计划 面上项目,‘’双层规划模型研究及其在契约理论中的应用‘’, 2021-2023. 50 万 (结题)

主持：国家自然科学基金 面上项目, "基于变分分析的分裂算法线性收敛率研究'', 2020 - 2023. 52 万  (在研)

主持：国家自然科学基金 青年项目, "关于规模化双层规划问题的最优性与算法研究'', 2017 - 2019. 20 万. (结题)

主持：Research Grants Council of Hong Kong, "Linear convergence of the (randomized block coordinate) proximal gradient methods via variational analysis'', 2018 - 2021. 30 万. (离职中止)

科研奖项

国家自然科学基金 优青项目（ 2023）

广东省科技厅 青年科技创新奖（ 2022）

广东省自然科学基金 杰青项目（ 2022）

深圳市优秀科技创新人才培养 优青项目（ 2021）

中国运筹学会 青年科技奖 (2020）

南方科技大学 理学院青年科研奖 (2020)

教学

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

课题组成员

研究助理教授：

尧伟 博士（ 2022.6 - 至今）, 武汉大学 (本科), 香港中文大学 (博士) ，南方科技大学 (博士后研究员) 

长期访问学者:

晁棉涛 副教授  (2022.1 - 2023.1) ,  广西大学

胡清洁 教授 (2022.1 - 2023.1) ,  桂林电子科技大学 

白旷 助理教授 (2022.2 - 2022.8),  香港理工大学

朱江醒 副教授  (2021.1 - 2022.1) ,  云南大学 

李培丽 副教授  (2023.7 - 至今 ) 河南大学

博士后研究人员:

尧伟 博士（ 2020.4 - 2022.5）, 武汉大学  (本科), 香港中文大学  (博士)

罗璇 博士 ( 2021.8 -   至今）,  华中科技大学  (本科),  香港城市大学  (博士) 

胡春海 博士（ 2022.6 - 至今）, 云南大学   (本科/博士)

毛伟豪 博士 (2023.3 - 至今）, 武汉理工大学 (本科), 厦门大学   (博士)

尹海安 博士 (2023.7 - 至今）, 东南大学 (本科), 南方科技大学 (硕士/博士) 

博士研究生:

尹海安（ 2019.9 - 2023.6）, 东南大学  (本科),  南方科技大学 (硕士). 南科大 2023 届优秀博士学位论文 ，中国运筹学会第一届“运筹新人”邀请报告，现深圳国家应用数学中心博士后研究员

宋一侠（ 2021.9 - 至今）, 郑州大学 (本科), 南方科技大学 (硕士) 

杨佩璇 ( 2022.9 - 至今) ，吉林大学  (本科), 南开大学  (硕士)

白晓宁 (2023.9 - 至今) ，东北大学（本科）, 北京理工大学（硕士）

张旅刚（ 2024.9 - ） ，吉林大学（本科） ，直博  

曹啟超（ 2024.9 - ）, 电子科技大学 (本科/硕士) 

联合培养博士研究生:

马耀帅 (主导师：鹏城实验室 王晓 教授, 2022.9 - 至今),  辽宁师范大学 (本科), 广西大学 (硕士)

张艺萱 (主导师：香港理工大学 陈小君 教授, 2022.9 - 至今), 北京师范大学  (本科),  南方科技大学 (硕士) 

李珊珊 (主导师：鹏城实验室 王晓 教授, 2023.9 - ),  电子科技大学  (硕士)

硕士研究生：

宋一侠（ 2018.9 - 2021.7）, 郑州大学  (本科), 现南方科技大学博士研究生

余承铭（ 2019.9 - 2023.6）, 大连理工大学  (本科)

张艺萱（ 2020.9 - 2022.7）,  北京师范大学  (本科)，南科大理学院2022届优秀毕业生，南科大2022届优秀硕士学位论文 ，现香港理工大学博士研究生

孙凯祺（ 2021.9 - 至今）, 湘潭大学 (本科)

王非凡 (2022.9 - 至今)，南方科技大学 (本科)

陈澄（ 2022.9 - 至今）, 杭州电子科技大学 (本科)

章志豪 (2022.9 - 至今 )，吉林大学 (本科) 

访问博士研究生:

杨振平（ 2019.1 - 2019.7）, 上海大学 ，现 嘉应学院 副教授

曾尚志（ 2019.9 - 2020.3, 2020.7- 2021.9）,  香港大学，现维多利亚大学PIMS博士后研究员,  合作导师Jane Ye教授

丁彦昀（ 2020.6 - 2023.6）, 北京工业大学 ，现深圳职业技术学院讲师

马笑笑 （ 2020.8 - 2021.8）, 维多利亚大学

褚天舒（ 2023.3 - 至今）, 北京工业大学

发表论著

代表著作（ 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)