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Gratitude and Graph Theory in the Time of Coronavirus

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Holy Cow! We’re Going Online When? 

Tagged Division

Civil Engineering

Page Count

10

DOI

10.18260/1-2--37235

Permanent URL

https://peer.asee.org/37235

Download Count

393

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Paper Authors

biography

Gerald J. Wang Carnegie Mellon University Orcid 16x16 orcid.org/0000-0002-0631-011X

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Jerry Wang is an Assistant Professor of Civil and Environmental Engineering, and Mechanical Engineering (by courtesy) and Chemical Engineering (by courtesy), at Carnegie Mellon University. He received his BS in 2013 from Yale University (Mechanical Engineering, Mathematics and Physics), SM in 2015 from MIT (Mechanical Engineering), and PhD in 2019 from MIT (Mechanical Engineering and Computation). He performed postdoctoral research at MIT in Chemical Engineering. He is a member of the inaugural cohort of the Provost's Inclusive Teaching Fellowship at CMU, was the 2020 recipient of the Frederick A. Howes Scholar Award in Computational Science and the 2016 MIT Graduate Teaching Award in the School of Engineering, and is an alumnus of the Department of Energy Computational Science Graduate Fellowship and the Tau Beta Pi Graduate Fellowship.

Wang directs the Mechanics of Materials via Molecular and Multiscale Methods Laboratory (M5 Lab) at CMU, which focuses on computational micro- and nanoscale mechanics of fluids, soft matter, and active matter, with applications in Civil and Environmental Engineering across the nexus of water, energy, sustainable materials, and urban livability. The M5 Lab is particularly interested in particle-based simulations, systems out of equilibrium, uncertainty quantification in molecular simulations, and high-performance computing. He teaches courses in molecular simulation and computational/data science.

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Abstract

In this work, we describe two activities that we have designed – suitable for an introductory undergraduate course in computational and data science – that introduce rudimentary principles of graph theory. Both activities feature simple premises (yet have the potential for significant depth, depending on student interest and mathematical maturity), strengthen students’ abilities in mathematical and computational reasoning, and interweave timely “out-of-the-classroom” themes that will resonate in 2021 and beyond. We also provide qualitative results from the deployment of these activities in a sophomore-level civil and environmental engineering class.

Wang, G. J. (2021, July), Gratitude and Graph Theory in the Time of Coronavirus Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--37235

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