Tag: Research Initiatives
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Students showcase innovation at IOE Senior Design Expo
U-M IOE Senior Design Expo highlights graduating seniors’ real-world research and solutions.
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More efficient wind turbine reliability simulation
Digitally testing the reliability of large-scale structures can be computationally intensive, but a new method significantly boosts efficiency while maintaining accuracy.
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Estrada-Garcia awarded 2025 IES graduate and postdoctoral fellowship
Juan-Alberto Estrada-Garcia, a PhD student in the Department of Industrial and Operations Engineering has been awarded a 2025 U-M Institute for Energy Solutions Graduate and Postdoctoral Fellowship for his work in power systems amidst wildfires.
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Berahas named member of the Air Force Office of Scientific Research 2025 Young Investigator Program
Albert S. Berahas will use this opportunity to develop, analyze and implement algorithms for solving noisy constrained derivative-free optimization problems, prevalent in fields such as engineering design, medicine and machine learning.
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IOE students showcase research skills at fall Senior Design Expo
The biannual event illustrates U-M IOE seniors’ workforce preparedness by collaborating with industry partners.
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U-M IOE community excels at 2024 INFORMS Annual Meeting
The University of Michigan Industrial and Operations Engineering Department walked away with numerous awards, including an INFORMS Fellow Award for Amy Cohn and Magna Cum Laude status for the U-M INFORMS student chapter.
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IOE Symposium Highlights Undergraduate Research
The U-M IOE Undergraduate Research Symposium highlights undergraduate student research projects each fall. These include topics like AI in human factors engineering, exam room utilization at Michigan Medicine and much more.
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Berahas Receives ONR Grant to Develop Advanced Optimization Algorithms
The grant will fund the development of cutting-edge algorithms for solving complex nonlinear constrained stochastic optimization problems. Albert Berahas, and Micheal O’Neill will lead the research to advance optimization methods and address real-world challenges.
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Saif Benjaafar Named Distinguished Fellow of MSOM Society
The University of Michigan Industrial and Operations Engineering Professor has been named a Distinguished Fellow by the Manufacturing and Service Operations Management (MSOM) Society of the Institute for Operations Research and the Management Sciences (INFORMS).
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Industrial and Operations Engineering alum speaks at aviation conference
Sinan Abdulhak is presenting two research papers at the 2024 International Conference on Research in Air Transportation at the University in Singapore.
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IOE hosts its annual Senior Design Expo
The IOE Senior Design Expo highlights the research of its graduating seniors before they go off into the world to solve real world problems in industrial engineering and operations research.
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New statistical tool to distinguish shared and unique features in data from different sources
Personalized PCA method overcomes the challenges of heterogeneous data analysis
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An augmented reality assessment designed to test astronaut adjustment to gravity changes
It’s not safe to assume astronauts are ready for mission tasks following spaceflights.
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Researchers identify behaviors that lead to interprofessional collaboration within intensive care units
Through observations, clinician shadowing, and interviews with ICU personnel, the research team from the University of Michigan identified 18 distinct behaviors, which they divided into two categories labeled ‘enablers’ and ‘collaborative activities’.
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Michigan Engineering Professors to develop novel federated learning algorithms for distributed 3D printing
Kontar and Okwudire have received a grant from Cisco Systems Inc. to develop novel federated learning algorithms that address descriptive, predictive and prescriptive machine learning opportunities in large-scale distributed 3D printing.
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Salar Fattahi receives NSF CAREER Award for work in nonconvex problems in machine learning
Salar Fattahi discusses his award-winning CAREER proposal which aims to close the current gap between optimization and statistical learning.