Ph.D. Engineering Economic Systems and Operations Research, Stanford University
M.S. Engineering Economic Systems, Stanford University
B.S. Systems and Control, Huazhong University of Science and Technology

Yinyu Ye is currently a Fractional Professor at the School of Data Science of The Chinese University of Hong Kong, Shenzhen and a Fractional Professor at the Institute of Intelligent Computing of Shanghai Jiao Tong University. Previously, Professor Ye was the K. T. Li Chair Professor in the Department of Management Science and Engineering and the Institute for Computational and Mathematical Engineering at Stanford University.His current research topics include Continuous and Discrete Optimization, Data Science and Applications, Numerical Algorithm Design and Analyses, Algorithmic Game/Market Equilibrium, Operations Research and Management Science etc. and he was one of the pioneers of Interior-Point Methods, Conic Linear Programming, Distributionally Robust Optimization, Online Linear Programming and Learning, Algorithm Analyses for Reinforcement Learning and Markov Decision Process, and etc. He has received several scientific awards, including the 2006 INFORMS Farkas Prize (Inaugural Recipient) for fundamental contributions to optimization, the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the 2014 SIAM Optimization Prize awarded (every three years), etc. According to Google Scholar, his publications have been cited 59,000 times.

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.

(Partial presentation)