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: | [email protected] |
江波,博士,上海财经大学信息管理与工程学院教授,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Whitebox Advisors(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.上海财经大学青年创新团队项目,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-Rank Tensor Completion and Robust Tensor PCA, IEEE Journal of Selected Topics in Signal Processing, 12(6), 1390-1404, 2018.
B. Jiang*, T. Lin, S. Ma and S. Zhang, Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis, Computational Optimization and Applications, 72, 115–157, 2019.
D. Ge, L. Hu, B. Jiang, G. Su and X. Wu, Intelligent Site Selection for Bricks-and-Mortar Stores, Modern Supply Chain Research and Applications, 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 on Modern 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, published online, https://doi.org/10.1287/moor.2020.1103, 2021.
上海财经大学学术新人奖;
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);