教授简介 研究领域 学术成果
上海财经大学信息管理与工程学院长聘教授，博士生导师，副院长，滴水湖高级金融学院双聘教授。教育部“国家级人才项目”青年学者、上海市青年拔尖人才。
2013年获得美国明尼苏达大学博士学位。有近10篇论文发表于运筹优化与机器学习的国际顶级期刊《Operations Research》、《Mathematics of Operations Research》、《Mathematical Programming》、《SIAM Journalon Optimization》、《Journal of Machine Learning Research》。论文引用人包括多位冯·诺依曼理论奖(又被称为运筹管理学领域的“诺贝尔奖”)得主，美国三院院士等学术权威。帮助中国著名企业如京东、顺丰、永辉、太平洋保险等解决仓库优化、定价、选址、排班等问题中的核心难题，取得了良好的实践效果。获得了中国运筹学会青年科技奖、上海市自然科学奖二等奖、宝钢优秀教师奖，上海市教学成果一等奖等荣誉。现主持1项国家自然科学基金面上项目。
运筹优化、收益管理、机器学习等。
科研项目
1.国家自然科学基金重大项目课题，基于人工智能的数学规划算法，2024-01至2028-12，在研，主持
2.国家自然科学基金面上项目，数据驱动的收益管理研究：运筹学理论与算法，2022-01至2025-12，在研，主持
3.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，已结题，参与（排名2/10）
4.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，已结题，参与（排名4/10）
5.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，已结题，主持
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，已结题，主持
代表性论文
1. 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.
2. 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.
3. B. Jiang,S. Ma, and S. Zhang, Tensor Principal Component Analysis via Convex Optimization,Mathematical Programming,150, 423-457, 2015.
4. 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.
5. B. Jiang,Z. Li, and S. Zhang, On Cones of Nonnegative Quartic Forms,Foundations of Computational Mathematics, 17(1), 161-197, 2017.
6. 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.
7. 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.
8. B. Jiang,H.Wang, and S. Zhang, An Optimal High-Order Tensor Method for Convex Optimization,Mathematics of Operations Research,46(4),1390–1412,2021.
9. X. Chen*,B. Jiang*,T.Lin, and S. Zhang, Accelerating Adaptive Cubic Regularization ofNewton's Method via Random Sampling,Journal of Machine Learning Research,23(90),1-38,2022.
10. S.He,H.Hu,B. Jiang, andZ.Li,Approximating tensor normsviasphere covering: Bridging the gap between primal and dual,SIAM Journal on Optimization,33(3),2026-2088, 2023.
11. A. Desir*, V. Goyal,B. Jiang*, T. Xie and J. Zhang, Robust Assortment Optimization under the Markov Chain Choice Model,Operations Research,72(4), 1595–1614, 2024.
12. Q. Deng, Q. Feng, W. Gao, D. Ge,B. Jiang*, Y. Jiang, J. Liu, T. Liu, C. Xue, Y. Ye and C. Zhang,An Enhanced ADMM-based Interior Point Method for Linear and ConicOptimization,INFORMS Journal on Computing,accepted, 2024.
13. C. He, S. Pan, X. Wang, andB. Jiang*, Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity,Proceedings of 41stInternational Conference on Machine Learning (ICML), 2024.
14. J. Guan, S. He,B. Jiangand Z. Li, l_p sphere covering and approximating nuclear p-norm,Mathematics of Operations Research, accepted, 2024.
