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张进

姓名 张进
性别 发明专利4999代写全部资料
学校 南方科技大学
部门 数学系
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学历 版权登记666包过 代写全部资料
职称 Tenure-Track 副教授
联系方式 FacultyofScience,M621room.DepartmentofMathematics,SouthernUniversityofScienceandTechnology.
邮箱 zhangj9@sustech.edu.cn
   
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教师主页 团队成员 科研项目 研究领域 学术成果 教学 科研分享 新闻动态 疼痛医学中心 成果介绍 软件 毕业去向 加入我们 联系我们 张进 Google Scholar ResearcherID Tenure-Track 副教授 数学系 张进,籍贯安徽省安庆市岳西县,南方科技大学数学系/深圳国家应用数学中心 副教授,2007、2010年本科、硕士毕业于大连理工大学,2014年博士毕业于加拿大维多利亚大学。2015至2018年间任职香港浸会大学数学系,2019年初加入南方科技大学。致力于最优化理论和应用研究,代表性成果发表在Math Program、SIAM J Optim、Math Oper Res、SIAM J Numer Anal、J Mach Learn Res、IEEE Trans Pattern Anal Mach Intell,以及ICML、NeurIPS、ICLR等有重要影响力的最优化、计算数学、机器学习期刊与会议上。研究成果获得 中国运筹学会青年科技奖、广东省青年科技创新奖,主持 国家自然科学基金优青、天元重点、面上项目、广东省自然科学基金杰青项目、深圳市科技创新培养人才优青项目、以及科技部重点研发计划“数学与应用数学”专项课题。  Editoral Service: Associate Editor of Numerical Algebra, Control and Optimization (NACO) 数学系主页: https://math.sustech.edu.cn/c/zhangjin 个人简介 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 个人荣誉 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) 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.   Curriculum Vitae(pdf) 个人简介 研究领域 最优化理论:变分分析,非光滑分析,扰动分析(2010 - present, start this topic since entering the Ph.D. program in UViC) 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 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. 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. 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. 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  双层规划方法在机器学习中应用(2019 - present, start these two bilevel related topics since arriving at SUSTech) R.S. Liu, Y.H. Liu, S.Z. Zeng and J. Zhang*, Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond, Conference on Neural Information Processing Systems (NeurIPS) Spotlight (< 3% out of 9122 submissions) 2021 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 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 (广东省计算数学会青年优秀学术成果奖) 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, IEEE Transactions on Pattern Analysis and Machine Intelligence 2022. 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 2022b 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 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) 2022a 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) 2022b 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 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 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 2023a 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 2023b W. Yao, C.M. Yu, S.Z. Zeng and J. Zhang*, Constrained Bi-Level Optimization: Proximal Lagrangian Value function Approach and Hessian-free Algorithm, International Conference on Learning Representations (ICLR) spotlight presentation (<5% out of 7262 submissions), 2024  双层规划理论在经济学中应用 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, 2022a  基于变分分析的优化算法收敛分析(2015 - present, start this topic since arriving at HKBU) 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. 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. 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 (the most satisfied paper) B. Mordukhovich*, X.M. Yuan, S.Z. Zeng and J. Zhang*, A globally convergent proximal Newton-type method in nonsmooth convex optimization, Mathematical Programming 2022a  随机规划 / 鲁棒优化(2007 - present, start this topic since entering the master program in DUT) 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, 2022b 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. 学术成果 查看更多 张进博士一直致力于最优化理论和应用研究,代表性成果发表在Mathematical Programming、SIAM Journal on Optimization、Mathematics of Operations Research、SIAM Journal on Numerical Analysis、Journal of Machine Learning Research、IEEE Transactions on Pattern Analysis and Machine Intelligence、International Conference on Machine Learning、Conference on Neural Information Processing Systems等有重要影响力的应用数学、机器学习期刊与会议上。研究成果获得 中国运筹学会青年科技奖、广东省青年科技创新奖,主持 国家自然科学基金优青、天元重点、面上项目、广东省自然科学基金杰青项目、深圳市科技创新培养人才优青项目、以及科技部重点研发计划“数学与应用数学”专项课题。 新闻动态 更多新闻 2022年度广东省青年科技创新奖 2023-02-13 第七届中国运筹学会青年科技奖 2020-10-30 Conference on Advances in Nonsmooth Analysis and Applications 2019 2019-12-10 团队成员 查看更多 PrevNext UpDown 加入团队 长期招聘 研究助理教授/博士后 研究员: 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.招收2025级博士研究生: 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.  查看更多 联系我们 联系地址 Faculty of Science, M621 room. Department of Mathematics, Southern University of Science and Technology. 办公电话 0755-88015915 电子邮箱 zhangj9@sustech.edu.cn

张进