Jim Dai joined Cornell University in 2012 as a professor in the School of Operations Research and Information Engineering (ORIE). Prior joining Cornell, 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. He is a Special Term Professor at Tsinghua University. He was a James Riady Distinguished Visiting Professor in Decision Sciences at National University of Singapore (May 2009-Apr 2011), a visiting professor at Aarhus University (Oct 1998-Dec 1998) and Stanford University (Dec 1998-June 1999), and a visiting assistant professor at University of Wisconsin-Madison (Aug 1991-Dec 1991).
Dai is an elected fellow of Institute of Mathematical Statistics and an elected fellow of Institute for Operations Research and the Management Sciences (INFORMS).
Jim Dai studies applied probability models for eﬃcient resource allocations in processing networks that model service systems such as customer contact centers, data centers, hospital patient flow management, airline yield management, and ridesharing networks. Much of his research is motivated by the challenge of eﬃciently managing a finite capacity system facing a time-varying, uncertain load. He develops theory for using fluid limit to study stability of a processing network. He develops diffusion models such as piecewise Ornstein-Uhlenbeck processes and semimartingale reflecting Brownian motions for analy-sis and control of a processing networks. His recent focus is to use Stein's method both as an engineering tool to develop an approximation model and as a mathematical tool to establish error bound for the approximation.
At the undergraduate level, Professor Dai teaches Markov chain models (both discrete and continuous times) and their applications to supply chains, service systems, and manufacturing systems, and data centers. He taught Markov decision processes, a framework for optimal sequential decisions under uncertainty in a variety of settings including inventory control and revenue management. At Ph.D. level, he is interested in teaching applied probability courses including Applied Stochastic Processes (6500), Probability (6510), and Advanced Stochastic Processes (6540). In addition, he is interested in teaching Markov decision processes and approximate dynamic programming that cover both the mathematical foundation and eﬃcient algorithms for solving diﬃcult problems of realistic sizes.
Dai currently serves on the Advisory Board for Engineering Systems and Design at Singa-pore University of Technology and Design. He serves as Editor-in-Chief for Mathematics of Operations Research, as an Advisory Editor for Stochastic Systems, and as an Associate Editor for Probability Survey and for Journal of Applied Probability. He currently also serves on IMS Committee on Special Lectures. He served as an Area Editor for Operations Research, as a Series Co-Editor for Handbooks in Operations Research and Management Science, and as an Associate Editor for Management Science and for Queueing Systems. Dai served on INFORMS Lanchester Prize Committee, on INFORMS John von Neumann Theory Prize Committee, and on editor-in-chief search committee for Mathematics of Op-erations Resesrch and for Stochastic Systems.
- 1992. "Reflected Brownian motion in an orthant: numerical methods for steady-state analysis." Annals of Applied Probability 2: 65-86. .
- 1995. "On positive Harris recurrence of multiclass queueing networks: a unified approach via fluid limit models." Annals of Applied Probability 5 (1): 49-77. .
- 2000. "The throughput of data switches with and without speedup." IEEE INFORCOM 2: 556-564. .
- 2005. "Maximum pressure policies in stochastic processing networks." Operations Research 53 (2): 197-218. .
- 2017. "Inpatient Bed Overflow: An Approximate Dynamic Programming Approach, submitted for publication." . .
Selected Awards and Honors
- NSF Young Investigator Award (National Science Foundation) 1994
- The Best Publication Award (Applied Probability Society of INFORMS) 1997
- The Erlang Prize (Applied Probability Society of INFORMS) 1998
- IBM Faculty Award (IBM) 2003
- Markov Lecture at INFORMS Phoenix Meeting (Applied Probability Society of INFORMS) 2012
- BS (Mathematics), Nanjing University, 1982
- MS (Mathematics), Nanjing University, 1985
- Ph D (Mathematics), Stanford University, 1990