DAI, Jiangang Jim
Dean, Presidential Chair Professor
Ph.D. Mathematics, Stanford University, 1990
M.S. Mathematics, Nanjing University, 1985
B.S. Mathematics, Nanjing University, 1982
Professor Jiangang Jim Dai is a Presidential Chair Professor at The Chinese University of Hong Kong, Shenzhen. Professor Dai received his BA and MA in Mathematics from Nanjing University and his Ph.D. in Mathematics from Stanford University. He is also on the faculty of Cornell University, where he is the Leon C. Welch Professor of Engineering in the School of Operations Research and Information Engineering. Prior joining Cornell in 2012, he held the Chandler Family Chair of Industrial and Systems Engineering at Georgia Institute of Technology, where he was a faculty member from 1990 to 2012.
Professor Dai is an international leading scholar in operations research. His main research direction is on stochastic processing networks. These mathematical models are used to help design, control and optimize complex systems, including semiconductor production lines, digital communication networks, data centers, customer call centers, hospital patient flow management, and ride-hailing platforms. The common challenge for these systems is to manage limited system resources effectively to meet changing and uncertain environments and to provide optimal services. Most of his former PhD students obtained faculty positions at internationally renowned universities.
Professor Dai has received a number of awards for his research contributions. He was honored with the 1994 Young Investigator Award (formerly the presidential Young scientist Award) and the 1998 Erlang Award from the INFORMS Applied Probability Society for his outstanding academic achievement. In 1997 and 2017, Professor Dai was awarded the Best Paper Award by the INFORMS Applied Probability Society. He is the only scholar to have won this award twice. In 2018, Professor Dai received the ACM SIGMETRICS Achievement Award. Professor Dai served as the Editor-In-Chief for Mathematics of Operations Research (MOR) from 2012 to 2019.
Submitted Paper for Publications
1. J.G. Dai and M Gluzman, Queueing Network Controls via Deep Reinforcement Learning, https://arxiv.org/abs/2008.01644
1. J.G. Dai and Pengyi Shi, Inpatient Overflow: An Approximate Dynamic Programming Approach, Manufacturing & Service Operations Management, Vol. 21, No. 4, 2019.
2. A Braverman, J.G. Dai, X Liu, and L Ying, Empty-car routing in ridesharing system, Operations Research 67 (5), 1437-1452, 2019.
3. Anton Braverman, J.G. Dai and Jiekun Feng, Stein's method for steady-state diffusion approximations: an introduction through the Erlang-A and Erlang-C models, Stochastic Systems, 6, 301-366, 2016.
4. J.G. Dai and Wuqin Lin, Maximum Pressure Policies in Stochastic Processing Networks, Operations Research, Vol. 53, 197-218, 2005.
5. J.G. Dai and B Prabhakar, The throughput of data switches with and without speedup, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications, 2000.
6. J.G. Dai, On positive Harris recurrence of multiclass queueing networks: a unified approach via fluid limit models, Annals of Applied Probability, 5, 49-77, 1995.
7. J.G. Dai and J. M. Harrison, Reflected Brownian motion in an orthant: numerical methods for steady-state analysis, Annals of Applied Probability, 2, 65-86, 1992.
Dai's papers listed on ORCID.