菜单总览
— 优秀师资 —

张树中

职位:

校长讲席教授

教育背景:

博士 (伊拉斯姆斯大学)

理学学士 (复旦大学)

研究领域
优化,运筹学,数据分析,生物信息学,金融工程,信号和图像处理
个人网站

http://www.menet.umn.edu/~zhangs/

Email

zhangs@cuhk.edu.cn

个人简介:


张树中教授,男,1963年10月出生。张树中1980至1984年在上海复旦大学数学系本科学习。而后在复旦大学数学所运筹控制专业研究生学习。1988年赴荷兰学习,于1991年在Erasmus大学的Tinbergen学院获计量经济与运筹学博士。同年获荷兰Groningen大学教职。他于1993年受聘返回Erasmus大学计量经济研究所任教。于1999年获Erasmus大学最佳研究奖(全校每年仅一人获此奖),并于同年被评为全荷兰前40名经济学家中的第6名。张树中教授于1999年回香港中文大学系统工程与工程管理学系任教,2001年获香港中文大学校长模范教学奖,2003年获中文大学青年研究奖。张树中教授于2011年赴美国明尼苏达大学任教,时值该校工业与系统工程系创系,张树中教授任该系创系系主任。

张树中教授在运筹学与最优化的理论和方法方面有着长期深入的研究,亦对运筹优化的应用有着浓厚兴趣和广泛经验。其研究涵括基因表达分析与疾病诊断、信号处理和频谱管理、金融投资模型和随机优化、风险收益管理和稳健优化、经济和对策论中的均衡和效率计算问题、算法软件设计等领域。张树中教授迄今为止已发表了140余篇学术论文和专著,并多次受邀在国际重要学术会议做大会报告。在非凸二次规划和非凸多项式优化方面,张教授发展了精确求解非凸二次规划问题的秩一矩阵分解方法,提出了求解非凸多项式优化问题的一系列新算法,引领了该领域的发展。张教授发展了多项式和张量优化模型的近似计算方法,也发展了目前唯一能求解任意次多项式优化模型有近似比保证的近似算法。这些非凸优化模型可以应用到众多的组合问题和图论问题、信号处理中的无线传感器定位及航空公司的收益管理等问题。因为对非凸多项式优化问题的理论与算法的杰出研究,张教授受邀在2009年芝加哥召开的三年一届的国际数学规划大会上作50分钟大会特邀报告。张树中教授的前博士生Jos Sturm根据他们共同发明的一系列求解半正定规划问题的原始对偶内点算法开发出了SeDuMi,是国际著名的优化软件之一。该软件自问世以来被引用5000多次。张树中教授和他合作者应用半定规划的对偶性理论,在理论上和实践上彻底解决了求解随机线性二次最优控制模型的计算问题,其结果在2003年获得了工程与应用数学协会(SIAM)最佳论文奖。张树中教授和罗智泉教授合作将泛函分析中的有关理论应用到信号处理领域,对目前信号处理中引人关注的动态频谱管理问题提出了解决方案。其研究结果在2009年获得了国际电气和电子工程师学会(IEEE)信号处理学会最佳论文奖。张树中教授于2016年获国际信号处理协会信号处理杂志最佳论文奖。近年来,张树中教授和他的学生们在采用低阶方法计算大规模优化模型上取得若干突破性进展,尤其在求解大数据分析中产生的非凸优化模型(包括张量计算模型)的结果,引起同行兴趣,曾受邀于2016年在日本东京举行的国际连续优化会议(三年一届)上作1小时大会报告。张树中教授曾任中国矿业大学管理学院的名誉院长 (2003-2006),也长期被复旦大学、中国科学院、清华大学、上海大学、上海财经大学等高校聘为客座教授。张树中教授是国际上许多重要期刊的编委,包括INFORMS学会旗下的Operations Research和Management Science。


学术著作:


代表性学术著作

 

1. B. Jiang, F. Yang, and S. Zhang, Tensor and Its Tucker Core: the Invariance Relationships. To appear in Numerical Linear Algebra with Applications.

2. B. Chen, S. He, Z. Li, and S. Zhang, On new classes of nonnegative symmetric tensors, SIAM Journal on Optimization, 27 (1), 292-318, 2017.

3. B. Jiang, Z. Li, and S. Zhang, On Cones of Nonnegative Quartic Forms, Foundations of Computational Mathematics, 17, 161-197, 2017.

4. T. Lin, S. Ma and S. Zhang, An Extragradient-Based Alternating Direction Method for Convex Minimization, Foundations of Computational Mathematics, 17, 35-59, 2017.

5. B. Jiang, S. Ma, M. Hardin, L. Qiao, J. Causey, I. Bitts, D. Johnson, S. Zhang and X. Huang, SparRec: An effective matrix completion framework of missing data imputation for GWAS, Scientific Reports, 6, Article Number: 35534 (2016).

6. X. Gao and S. Zhang, First-Order Algorithms for Convex Optimization with Nonseparate Objective and Coupled Constraints, Journal of Operations Research Society of China, DOI: 10.1007/s40305-016-0131-5, June 2016.

7. T. Lin, S. Ma, and S. Zhang, Iteration Complexity Analysis of Multi-Block ADMM for a Family of Convex Minimization without Strong Convexity, Journal of Scientific Computing, 69 (1), 52-81, 2016.

8. S. Tao, D. Boley and S. Zhang, Local Linear Convergence of ISTA and FISTA on the LASSO Problem, SIAM Journal on Optimization, 26 (1), 313-336, 2016.

9. Y. Liu, S. Ma, Y. Dai and S. Zhang, A Smoothing SQP Framework for a Class of Composite Lq Minimization over Polyhedron, Mathematical Programming, 158 (1-2), 467-500, 2016.

10. B. Jiang, Z. Li and S. Zhang, Characterizing Real-Valued Multivariate Complex Polynomials and Their Symmetric Tensor Representations, SIAM Journal on Matrix Analysis and Applications, 37 (1), 381-408, 2016.

11. T. Lin, S. Ma, and S. Zhang, On the Sublinear Convergence Rate of Multi-block ADMM, Journal of Operations Research Society of China, 3 (3), 251-274, 2015.

12. S. Ma, D. Johnson, C. Ashby, D. Xiong, C. L. Cramer, J. H. Moore, S. Zhang, and X. Huang, SPARCoC: a new framework for molecular pattern discovery and cancer gene identification, PLOS ONE, 10 (3): e0117135. DOI: 10.1371/journal.pone.0117135. Published online on March 13, 2015.

13. Z. Li, A. Uschmajew, and S. Zhang, Linear Convergence Analysis of the Maximum Block Improvement Method for Spherically Constrained Optimization, SIAM Journal on Optimization, 25(1), 210-233, 2015.

14. B. Chen, Z. Li, and S. Zhang, On tensor Tucker decomposition: the case for an adjustable core size, Journal of Global Optimization 62 (4), 811-832, 2015.

15. T. Lin, S. Ma, and S. Zhang, On the Global Linear Convergence of the ADMM with Multi-Block Variables, SIAM Journal on Optimization, 25 (3), 1478-1497, 2015.

16. B. Jiang, S. Ma, and S. Zhang, Tensor Principal Component Analysis via Convex Optimization, Mathematical Programming, 150, 423-457, 2015.

17. X. Huang et al., Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm, BioData Mining, 8 (7) DOI 10.1186/s13040-015-0037-5, 2015.

18. B. Jiang, S. Ma, and S. Zhang, Alternating Direction Method of Multipliers for Real and Complex Polynomial Optimization Models. Optimization, 63 (6), 883-898, 2014.

19. B. Jiang, Z. Li, and S. Zhang, Approximation Methods for Complex Polynomial Optimization, Computational Optimization and Applications, 59 (1), 219-248, 2014.

20. S. He, B. Jiang, Z. Li, and S. Zhang, Probability Bounds for Polynomial Functions in Random Variables, Mathematics of Operations Research, 39 (3), 889-907, 2014.

21. S. I. Birbil, J. B.G. Frenk, J. Gromicho, and S. Zhang, A Network Airline Revenue Management Framework Based on Decomposition by Origins and Destinations, Transportation Science, 48 (3), 313-333, 2014.

22. S. He, Z. Li, and S. Zhang, General Constrained Polynomial Optimization: an Approximation Approach, Mathematics of Computation, S 0025-5718(2014)02875-5. Article electronically published on July 24, 2014.

23. S. He, B. Jiang, Z. Li and S. Zhang, Moments Tensors, Hilbert's Identity, and k-wise Uncorrelated Random Variables, Mathematics of Operations Research, 39 (3), 775-788, 2014.

24. M. H. Wong and S. Zhang, On Distributional Robust Probability Functions and Their Computations, European Journal of Operational Research, 233, 23-33, 2014.

25. X. Huang et al., No-boundary thinking in bioinformatics research, BioData Mining, 6 (19), 2013.

26. Y.W. Huang, D. P. Palomar, and S. Zhang, Lorentz-Positive Maps and Quadratic Matrix Inequalities with Applications to Robust MISO Transmit Beamforming, IEEE Transaction on Signal Processing, 61 (5), 1121-1130, 2013.

27. X. Chen, J. Peng and S. Zhang, Existence of Sparse Solutions to the Standard Quadratic Programming with Random Matrices, Mathematical Programming, Ser. A, 141, 273-293, 2013.

28. A. Aubry, A. De Maio, B. Jiang, and S. Zhang, Ambiguity Function Shaping for Cognitive Radar via Complex Quartic Optimization, IEEE Transaction on Signal Processing, 61, 5603-5619, 2013.

29. S. He, X. G. Wang, and S. Zhang, On a Generalized Cournot Oligopolistic Competition Game, Journal of Global Optimization, 56 (40), 1335-1345, 2013.

30. S. He, Z. Li, and S. Zhang, Approximation Algorithms for Discrete Polynomial Optimization, Journal of Operations Research Society of China, 1, 3-36, 2013.

31. M. H. Wong and S. Zhang, Computing Best Bounds for Nonlinear Risk Measures with Partial Information. Insurance: Mathematics and Economics, 52 (2), 204-212, 2013.