Dr. Eunshin Byon is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan, Ann Arbor, USA. She received her Ph.D. degree in Industrial and Systems Engineering from the Texas A&M University, College Station, USA, and joined the University of Michigan in 2011.
Importance sampling has been used to improve the efficiency of simulations where the simulation output is uniquely determined, given a fixed input. We extend the theory of importance sampling to estimate a system’s reliability with stochastic simulations. Thanks to the advance of computing power, stochastic computer models are employed in many applications to represent a complex system behavior. More
To quantify and minimize the uncertainties in the design and operational stage, we model and analyze the dependency of wind turbine responses (e.g., power generation, loads and condition monitoring sensor measurement) on operating conditions and the interactions among turbines. Our research entails several areas… More
Extreme weather events, such as hurricanes, can disrupt how healthcare services are delivered by damaging the infrastructure they depend on. Natural disasters can force hospitals to evacuate. However, evacuation is not without risk. At this seminar, E²SHI Fellow Meghan McGinty will discuss how decisions to either evacuate hospitals or shelter-in-place (continue serving patients on site) were made during Hurricane Sandy in 2012 – and what we can learn from this experience to better prepare for future extreme weather events.
Presenter: Meghan McGinty is a PhD candidate in the Department of Health Policy and Management at the Johns Hopkins Bloomberg School of Public Health. Her research focuses on public health emergency preparedness and response, disaster resilience, and climate change. She is a 2013-14 E2SHI Fellowship recipient. Learn more about Meghan’s research
Labor Cost Accounting for Small Differences in Operating Room Time Such as From Lean Methods