姓名: | 江波 |
最后学位: | |
职称: | 教授 |
公共职务: | |
导师岗位: | 博导 |
办公室: | 611 |
电话: | 65900131 |
Email: | jiang.bo@mail.shufe.edu.cn |
江波,博士,betvictot官网教授,于2013年在美国明尼苏达大学工业与系统工程系获得博士学位,导师张树中教授。主要研究领域包括优化理论,收益管理,组合投资优化,信号处理等。在运筹优化的国际一流杂志Operations Research, Mathematics of Operations Research, Mathematical Programming, SIAM Journal on Optimizatoin等发表过多篇论文。现为美国数学会旗下 mathmatical reviews 的评论员, 担任过Management Science, Mathematics of Operations Research, SIAM Journal on Optimization等著名期刊的匿名审稿人。曾在美国对冲基金公司WhiteboxAdvisors(该基金旗下管理资产约45亿美元)担任暑期研究员,从事鲁棒组合投资的研究工作。近期的主要研究课题为多维数据(张量)优化的理论和实际应用。
非线性最优化算法与大数据
随机过程与动态规划
博弈论
高级运筹学
最优化理论
优化理论与算法
管理学前沿与科学方法论
1.国家自然科学原创探索计划项目,大规模优化算法的理论与应用,2021-01至2023-12,300万元,在研,参与(排名2/10)
2.betvictot官网青年创新团队项目,基于大数据的收益管理模型及方法的研究,2020-01至2024-12,100万元,在研,主持
3.国家自然科学基金重点项目,大数据驱动的优化建模与高效算法,2019-01至2023-12,250万元,在研,参与(排名4/10)
4. 国家自然科学基金面上项目,非负共轭多项式:张量表达,最优化算法及应用,2018-01至2021-12,48万元,在研,主持
5. 国家自然科学基金面上项目,压缩感知和稀疏优化中的非凸优化算法设计,2015-01至2018-12,60万元,已结题,参与
6. 国家自然科学基金青年项目, 低秩张量优化问题的模型、算法及应用,2015-01至2017-12,22万元,结题,主持
· 2011/03-2013/09, 美国明尼苏达大学(University of Minnesota),工业与系统工程系,博士, 导师: 张树中 教授
· 2008/08-2011/02, 香港中文大学,系统工程与工业工程系,攻读博士课程, 导师: 张树中 教授
· 2005/09-2008/07, 复旦大学,管理科学系,硕士, 导师: 黄学祥 教授
· 2001/09-2005/07, 华东师范大学,数学系,学士
A. Aubry, A. De Maio, B. Jiang, and S. Zhang, Ambiguity Function Shaping for Cognitive Radar Via Complex Quartic Optimization, IEEE Transactions on Signal Processing, 61, 5603-5619, 2013.
B. Jiang, S. He, 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.
B. Jiang, Z. Li, and S. Zhang, Approximation Methods for Complex Polynomial Optimization, Computational Optimization and Applications, 59, 219-248, 2014.
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.
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.
B. Jiang, S. Ma, and S. Zhang, Tensor Principal Component Analysis via Convex Optimization, Mathematical Programming, 150, 423-457, 2015.
X. Gao, B. Jiang*, and S. Tao, Recovering Low-Rank Tensors with Applications in Tensor Completion, Pacific Journal of Optimization, 11(2), 385-402, 2015.
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.
J. Hu, B. Jiang, X. Liu and Z. Wen, A Note on Semidefinite Programming Relaxations for Polynomial Optimization over A Single Sphere, Science China Mathematics, 59, 1543-1560, 2016.
B. Jiang, S. Ma, M. P. 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, 35534, 2016.
B. Jiang, Z. Li, and S. Zhang, On Cones of Nonnegative Quartic Forms, Foundations of Computational Mathematics, 17(1), 161-197, 2017.
B. Jiang*, F. Yang and S. Zhang, Tensor and Its Tucker Core: The Invariance Relationships, Numerical Linear Algebra with Applications, 24(3), e2086, 2017.
T. Fu, B. Jiang*, and Z. Li, Approximation algorithms for optimization of real-valued general conjugate complex forms, Journal of Global Optimization, 70, 99–130, 2018.
X. Gao, B. Jiang*, and S. Zhang, On the Information-Adaptive Variants of the ADMM: an Iteration Complexity Perspective, Journal of Scientific Computing, 76, 327–363, 2018.
B. Jiang, S. Ma, and S. Zhang, Low-M-RankTensor Completion and Robust Tensor PCA, IEEEJournal of Selected Topics in SignalProcessing, 12(6), 1390-1404, 2018.
B. Jiang*, T. Lin, S. Ma and S. Zhang, StructuredNonconvex andNonsmooth Optimization: Algorithms and Iteration ComplexityAnalysis, Computational Optimization andApplications, 72, 115–157, 2019.
D. Ge, L. Hu, B. Jiang,G. Su and X. Wu, Intelligent Site Selection for Bricks-and-Mortar Stores, ModernSupply Chain Research andApplications, 1(1), 88-102, 2019.
X. Zhu, Q. Chang, and B. Jiang, Introduction to High-Order Optimization Methods, OR Transactions, 23 (3): 63-76, 2019 (Chinese).
B. Jiang, T. Lin, and S. Zhang, A Unified Adaptive Tensor Approximation Scheme to Accelerate Composite Convex Optimization, SIAM Journal on Optimization, 30(4), 2897-2926, 2020.
Q. Deng, J. Gao, D. Ge, S. He, B. Jiang, X. Li, Z. Wang, C. Yang, and Y. Ye, A Survey onModern Optimization Theory and Applications, Science China Mathematics, 50(7), 899-968, 2020 (Chinese).
X. Chen, S. He, B. Jiang, C. Ryan and T. Zhang, The discrete moment problem with nonconvex shape constraints, Operations Research, 23 (3): 63-76, 2021.
B. Jiang, H. Wang, and S. Zhang, An Optimal High-Order Tensor Method for Convex Optimization, Mathematics of Operations Research, publishedonline, https://doi.org/10.1287/moor.2020.1103, 2021.
betvictot官网学术新人奖;
中国运筹学会青年科技奖;
上海市青年拔尖人才;
上海市高校特聘教授(东方学者);
上海市科学技术奖自然科学奖二等奖 (排名:2/2);