Research Projects & Publications
Vision Transformers, Explained & Compared
During my post-bachelors appointment at Los Alamos National Laboratory, I developed four tutorials explaining the internal mechanics of the vision transformer machine learning architecture. These tutorials feature functional code and mathematical explanations. The Vision Transformers, Explained series was published on Towards Data Science and selected as an Editor’s Pick.
Image-to-Scalar Regression Neural Networks
During my post-bachelors appointment at Los Alamos National Laboratory, I worked on developing and implementing neural network explainability/sensitivity measures on image-to-scalar regression models. These models are used for calibration of a tensile plasticity (TePla) damage model simulating the spallation in copper under high-explosive shock loading.
This work was presented as a poster at the 2023 Conference for Data Analysis (Feb. 2023). Additionally, this work was also presented at the 2023 American Society of Mechanical Engineers (ASME) Verification, Validation, and Uncertainty Quantification (VVUQ) Symposium (May 2023), and is published in the associated conference proceedings.
Aviation Surface Markings
For three years, I worked with a student team of Michigan Technological University (MTU)’s Built World Enterprise (BWE) to develop the Runway Intersection Marking. This new aviation surface marking combined insights from aviation and human factors professionals to reduce the risk of runway incursions and other unsafe events at high risk intersections.
This work was awarded first place in the 2020 Airport Cooperative Research Program (ACRP)’s University Design Competition in the Runway Safety/Runway Incursions/Runway Excursions Category, and the 2021 Airport Cooperative Research Program’s Next Steps Grant.