Ton Dieker's Homepage

I'm a Professor in the IEOR department at Columbia University. I am affiliated with the Data Science Institute.

Research interests

My research focuses on computational stochastic modeling, with particular emphasis on computer simulation algorithms and stochastic networks. My work is motivated by applications to business processes, workforce management, and service systems.

Group members

• Yunhao Yan (PhD student, with Henry Lam)
• Zitong Wang (PhD student, with Henry Lam)

Former group members

• Ben Cousins (postdoc, with Alex Andoni)
• Guido Lagos Barrios (PhD student)
• Richard Birge (PhD student)
• Tonghoon Suk (PhD student)
• Xuefeng Gao (PhD student, with Jim Dai)
• Jinwoo Shin (postdoc, with Prasad Tetali)

Brief biography

Ton Dieker is a Professor of Industrial Engineering and Operations Research at Columbia University and a member of the university’s Data Science Institute. He earned his M.Sc. from VU Amsterdam in 2002 and his Ph.D. from the University of Amsterdam in 2006. Before joining Columbia, he held a faculty position at Georgia Tech, where he was the Fouts Family Associate Professor. His research focuses on applied probability and its intersections with data science and operations research. He has received several honors, including the Goldstine Fellowship from IBM Research, the Erlang Prize from the INFORMS Applied Probability Society, and the Presidential Early Career Award for Scientists and Engineers (PECASE). In addition, he has contributed to the academic community through editorial roles with journals in Operations Research and Applied Probability. He co-authored "QPLEX: A Computational Modeling and Analysis Methodology for Stochastic Systems" with Steven T. Hackman, published by Springer Nature in 2025. This book introduces a computational framework for modeling and analyzing nonstationary stochastic systems.