Portland, Oregon
June 23, 2024
June 23, 2024
June 26, 2024
NSF Grantees Poster Session
5
10.18260/1-2--46755
https://peer.asee.org/46755
61
Zachary del Rosario is an Assistant Professor of Engineering and Applied Statistics at Olin College. His goal is to help scientists and engineers reason under uncertainty. Zach uses a toolkit from data science and uncertainty quantification to address a diverse set of problems, including reliable aircraft design and AI-assisted discovery of novel materials.
Variability is ubiquitous, but often ignored in engineering. Loading conditions, material properties, and human behavior all exhibit variability, but are often treated with fixed constants in engineering analysis. A first step towards improving the treatment of variability is to understand the conditions under which a person recognizes the consequences of variability and chooses an analysis to mitigate negative consequences---a process called targeting variability. We provide updates on Year 2 of our project, including the development of an instrument to measure the targeting behavior.
Del Rosario, Z., & Ryu, J., & Saur, E. (2024, June), Board 190: A Mixed-Methods Study of Statistical Thinking in Engineering Practice Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46755
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