معرفی
Pierre L'Écuyer is a Full Professor in the Department of Computer Science and Operational Research at the Faculty of Arts and Sciences, University of Montreal. He holds a Canada Research Chair in Stochastic Simulation and Optimization and is a member of GERAD and CIRRELT research centers. His office is located at André-Aisenstadt building, room 3361, and he can be reached at 514 343-2143.
Dr. L'Écuyer received his Baccalauréat in mathematics, Master's in operational research, and PhD in computer science with focus on operational research, all from the University of Montreal. His academic journey has led him to become one of the world's most influential researchers in stochastic simulation.
His research focuses on stochastic systems modeling and simulation, with particular expertise in random number generation, quasi-Monte Carlo methods, simulation efficiency improvement, sensitivity analysis, and optimization. His work has practical applications in call centers, finance, communication systems, and revenue management. Analysis of his recent publications shows strong emphasis on randomized quasi-Monte Carlo methods, variance reduction techniques, and applications to complex optimization problems in service systems.
- Lifetime Professional Achievement Award from INFORMS (2020)
- Ranked among the most influential researchers worldwide by Mendeley/Elsevier (2019, 2020)
- ACM SIGSIM Distinguished Contribution Award (2016)
- Mercit Award from Canadian Operational Research Society (2014)
- Distinguished Service Award from INFORMS Simulation Society (2011)
- Urgel-Archambault Prize from ACFAS (2002)
Dr. L'Écuyer has supervised numerous PhD and Master's students working on topics ranging from random number generation to call center optimization. His current research projects, funded by NSERC and other organizations, focus on fundamental tools for stochastic simulation, with applications extending through 2030. He leads the SIMUL research laboratory which has developed several important software tools including SSJ (Stochastic Simulation in Java), TestU01, and RNGStreams.
