Calendar

Apr
10
Wed
2013
Workshop on Systems Methods for Understanding Obesity
Apr 10 @ 12:00 pm – Apr 11 @ 6:00 pm

The Education and Training Core (ETC) of the Johns Hopkins Global Center on Childhood Obesity (JHGCCO) is pleased to announce a training workshop entitled Agent-based and System Dynamics Models: New Tools for UnderstandingObesity. The workshop will begin at noon on Wednesday, April 10, and run until 6 pm on Thursday, April 11, with a dinner and reception on Wednesday night.

The workshop is intended for researchers, program staff, students, trainees, faculty and those with an interest in learning about how agent-based (ABM) and system dynamics (SD) models can be used to gain insights into the causes of, and potential solutions for, the obesity epidemic. The primary faculty for this workshop include Prof. Tak Igusa from the Johns Hopkins Systems Institute and the Whiting School of Engineering, and Prof. Thomas Glass from the Johns Hopkins Bloomberg School of Public Health. There will also be an invited lecture and discussion by Dr. Amy Auchincloss, Ph.D., MPH, Assistant Professor of Epidemiology and Biostatistics from Drexel University.

Mar
3
Tue
2015
Dr. Eunshin Byon to present two seminars on Mar 3 @ Ames Hall, Room 302
Mar 3 @ 12:00 pm – 3:00 pm

Dr. Eunshin Byon

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 for Reliability Evaluation with Stochastic Computer Models (12-1:30pm)
ABSTRACT:

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

 Data-driven Modeling and Analysis for Wind Power Systems (1:30-3pm)
ABSTRACT:

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

Center for Systems Science and Engineering