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\section{Education} | ||
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\skills{PhD Materials Science and Engineering}, \textit{University of Wisconsin-Madison} (GPA: 3.691 out of 4.0) \hfill May 2024 | ||
\skills{Ph.D. Materials Science and Engineering}, \textit{University of Wisconsin-Madison} (GPA: 3.691 out of 4.0) \hfill Aug 2024 | ||
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\skills{M.S. Materials Science and Engineering}, \textit{University of Wisconsin-Madison} (GPA: 3.691 out of 4.0) \hfill Dec 2020 | ||
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\skills{B.S. Engineering}, \textit{Fort Lewis College} (GPA: 3.99 out of 4.0) \hfill Dec 2017 | ||
\skills{B.S. Engineering}, \textit{Fort Lewis College} (GPA: 3.99 out of 4.0) \hfill Dec 2017 | ||
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\skills{ } |
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\section{Publications} | ||
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\begin{itemize} | ||
\item L. E. Schultz, B. Afflerbach, D. Morgan, \textit{Machine Learning Metallic Glass Critical Cooling Rates Through Atomistic and Molecular Dynamic Material Properties}, Pending publication. | ||
\item L. E. Schultz, Y. Wang, R. Jacobs, D. Morgan, \textit{Assessing Machine Learning Model Domains using Kernel Density Estimates}, Pending publication. | ||
\item L. E. Schultz, B. Afflerbach, D. Morgan, \textit{Machine Learning Metallic Glass Critical Cooling Rates Through Atomistic and Molecular Dynamic Material Properties}, Pending publication | ||
\item L. E. Schultz, Y. Wang, R. Jacobs, D. Morgan, \textit{Assessing Machine Learning Model Domains using Kernel Density Estimates}, Pending publication | ||
\item V. Agrawal et al. Accelerating Ensemble Error Bar Prediction with Single Model Fits, Computational Materials Science, Pending Publication | ||
\item J. Meng et al., Ultra-fast oxygen conduction through vacancy-mediated mechanism in Sillén Oxychlorides, Pending Publication | ||
\item B. Afflerbach et al., \textit{Machine Learning Prediction of the Critical Cooling Rate for Metallic Glasses from Expanded Datasets and Elemental Features}, Chemistry of Materials, DOI: 10.1021/acs.chemmater.1c03542 | ||
\item L. E. Schultz, B. Afflerbach, D. Morgan, I. Szlufarska, \textit{Molecular Dynamics Characteristic Temperatures for Predicting Metallic Glass Forming Ability}, Computational Materials Science, January 2022, DOI: 10.1016/j.commatsci.2021.110877 | ||
\item L. E. Schultz, B. Afflerbach, C. Francis, D. Morgan, I. Szlufarska, P. Voyles, \textit{Exploration of Characteristic Temperature Contributions to Metallic Glass Forming Ability}, Computational Materials Science, August 2021, DOI: 10.1016/j.commatsci.2021.110494 | ||
\item B. Afflerbach et al., \textit{Molecular simulation-derived features for machine learning predictions of metal glass forming ability.} Computational Materials Science, November 2021, DOI: 10.1016/j.commatsci.2021.110728 | ||
\item J. Xi et al., \textit{Microalloying effect in ternary Al-Sm-X (X = Ag, Au, Cu) metallic glasses studied by ab initio molecular dynamics.} Computational Materials Science, December 2020, DOI: 10.1016/j.commatsci.2020.109958 | ||
\item L. E. Schultz, T. J. Cogger, J. Schneider, R. Good, R. Rothschild, and W. Nollet, \textit{Design of torsional test stand for micro-newton force detection.} Aerodynamic Measurement Technology and Ground Testing Conference, June 2018, DOI: 10.2514/6.2018-3737 | ||
\item J. Schneider, L. E. Schultz, S. Mancha, E. Hicks, and R. N. Smith, \textit{Development of a portable water quality sensor for river monitoring from small rafts.} OCEANS 2016 MTS/IEEE Monterey, September 2016, DOI: 10.1109/OCEANS.2016.7761392 | ||
\end{itemize} | ||
\end{itemize} |
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