Dr. Michael E. Kuhl earned a Ph.D. in Industrial Engineering from North Carolina State University; an M.S. degree in Industrial Engineering and Operations Research from North Carolina State University; and a B.S. degree in Industrial Engineering from Bradley University (1992).
Dr. Kuhl’s research interests are in the field of simulation and operations research. This work focuses on stochastic input modeling for simulation including modeling and simulation of nonstationary arrival processes. In addition his work encompasses simulation modeling and optimization methodologies with application to healthcare, manufacturing, logistics, sustainability, and other industrial and service systems.
For more about Dr. Kuhl see his website: <people.rit.edu/mekeie>
· Kuhl, M.E., J.S. Ivy, E.K. Lada, N.M. Steiger, M.A. Wagner, and J.R. Wilson. (2010) Univariate Input Models for Stochastic Simulation, Journal of Simulation, 4, 81-97.
· Yang, S.J., A. Stotz, J. Holsopple, M. Sudit, and M. Kuhl. (2009) High Level Information Fusion for Tracking and Projection of Multistage Cyber Attacks, Information Fusion, 10 (1), 107-121.
· Bahaji, N. and M.E. Kuhl. (2008) A Simulation Study of New Multi-objective Composite Dispatching Rules, CONWIP, and Push Lot Release in Semiconductor Fabrication. International Journal of Production Research, 46 (14), 3801-3824.
· Carrano, A.L., M.E. Kuhl, and M.M. Marshall. (2008) Integration of an Experiential Assembly System Engineering Laboratory Module, International Journal of Engineering Education, 24 (5), 1012-1017.
· Kuhl, M.E., S.G. Sumant, and J.R. Wilson. (2006) An Automated Multiresolution Procedure for Modeling Nonhomogeneous Poisson Processes. INFORMS Journal on Computing, 18 (1), 3-18.