斯坦福大学工程经济系统和运筹学博士

斯坦福大学工程经济系统硕士

华中科技大学自动控制系学士

叶荫宇教授现为香港中文大学（深圳）数据科学学院特聘教授，上海交通大学智能计算研究院特聘教授。此前叶教授为斯坦福大学管理科学与工程系及计算数学工程研究院李国鼎讲席教授。他的主要研究方向为连续和离散优化、数据科学及应用、数字算法设计及分析、算法博弈及市场均衡、运筹及管理科学等；他和其他科学家开创了内点优化算法、锥规划模型、分布式鲁棒优化、在线线性规划和学习、强化学习和马可夫过程算法分析等。他多次获得科学奖项：包括2006年因在最优化领域做出的基础性贡献而获得的INFORMS Farkas奖（首届获奖者）、2009年因在运筹学和管理科学领域做出的根本性持续贡献而获得的约翰·冯·诺依曼理论奖、国际数学规划2012 Tseng Lectureship Prize（每三年颁发一次）、2014美国应用数学学会优化奖（每三年颁发一次）等。根据谷歌学术统计，目前他的文章被引用总计超过59000次。

1. “An O(n³L) potential reduction algorithm for linear programming,” Math Programming 50 (1991) 239-258.

2. “An O(n ^.5L)-iteration homogeneous and self-dual linear programming algorithm,” (Ye, Todd and Mizuno), Math Operations Res 19 (1994) 53-67.

3. “A primal-dual interior-point method whose running time depends only on the constraint matrix,” (Vavasis and Ye), Math Programming 74 (1996) 79-120.

4. “A Multi-Exchange Local Search Algorithm for the Capacitated Facility Location Problem,” (Zhang, Chen and Ye), Math Operations Research 30:2 (2005) 389-403.

5. “Disciplined convex programming,” (Grant, Boyd, Yinyu Ye), Global Optimization 84 (2006) 155-210.

6. “Distributionally Robust Optimization under Moment Uncertainty with Application to Data-Driven Problems,” (Delage and Ye), Operations Research 58:3 (2009) 595-612.

7. “Semidefinite Relaxation of Quadratic Optimization Problems,” (Luo, Ma, So, Ye, and Zhang), IEEE Signal Processing Magazine 27:3 (2010) 20-34.

8. “The Simplex and Policy-Iteration Methods are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate,” Math Operations Res, 36:4 (2011) 593-603.

9. “A Dynamic Near-Optimal Algorithm for Online Linear Programming” (Agrawal, Wang and Ye), Operations Research, 62(4) (2014) 876 - 890.

10. “The Direct Extension of ADMM for Multi-block Convex Minimization Problems is Not Necessarily Convergent,” (Caihua Chen, Bingsheng He, Yinyu Ye, Xiaoming Yuan), Math Programming. 155(1-2) (2016) 57-79.

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