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Mary Court

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Mary C. Court


Professor Emeritus

Links: Curriculum Vitae

Ph.D., Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute
M.S., Operations Management, Rensselaer Polytechnic Institute
B.S., Industrial and Management Engineering, Rensselaer Polytechnic Institute

Dr. Court joined the School of Industrial Engineering at the University of Oklahoma after completing her Ph.D. in Decision Sciences and Engineering Systems at Rensselaer Polytechnic Institute in 1993. Her main area of research is simulation with emphasis on the statistical analysis issues of simulation. She has received grants from government sources including the Federal Aviation Administration, the Department of Transportation and the United States Air Force. She is an active participant and has served as principle investigator on projects for the Oklahoma Transportation Center, the Center for Engineering Logistics and Distribution (CELDi) and the Center for Aircraft and Systems/Support Infrastructure. She has also been awarded several grants in engineering education.

Dr. Court was an industrial engineer for Sony Corporation of America and for the Tomahawk Cruise Missile Program at the Convair Division of General Dynamics. She was a manufacturing and systems engineer for the 688, Trident and Seawolf Submarine Programs at the Electric Boat Division of General Dynamics. She has also served as a consultant for several Oklahoma corporations.

Dr. Court was a National Defense and Engineering Fellow and a Laurie Rattner Manufacturing Systems Management Fellow. She received the Del and Ruth Krager Dissertation Award from Rensselaer Polytechnic Institute. She was awarded the University of Oklahoma’s Junior Faculty Award, the University of Oklahoma/Tulsa University’s T-Comm Faculty Award, and the University of Oklahoma/Student Chapter of the Institute of Industrial Engineers’ Best Professor Award. She is a member of the Institute of Industrial Engineers.

Simulation output analysis
Evacuation modeling and analysis
Transportation system viability
Lean manufacturing
Engineering education