EDUCATION

University of Delaware

Working Towards MS in Data Science & PhD in Applied Mathematics

Michigan Technological University

B.S. in Civil Engineering & B.S. in Applied Mathematics | GPA: 3.97

SKILLS: 

Advanced: Python, Git, Google Suite, Public Speaking, Technical Writing

Proficient: Matlab, Wolfram Mathematica, Julia,  Linux, LaTeX, Microsoft Office

ACCOLADES 

• First place in the 2020 Airport Cooperative Research Program’s University Design Competition in the Runway Safety/Runway Incursions/Runway Excursions Category

• Awarded 2021 Airport Cooperative Research Program’s Next Steps Grant

• Awarded 2022 Charles Knobloch Award, 2021 Mathematics Achievement Award, and 2020 Woman of Promise Award by the MTU Mathematical Sciences Department

• Certificates of Merit from the MTU Mathematical Sciences Department in 7 courses

  • MA3160 (Multivariable Calculus), MA2320 (Intro to Linear Algebra), MA3560 (Differential Equations w/ Modeling), MA3310 (Intro to Abstract Algebra), MA2600 ( Scientific Computing), MA4515 (Intro to Partial Differential Equations), & MA4410 (Complex Functions)

EXPERIENCE

GRADUATE RESEARCH ASSISTANT IN APPLIED MATH & PLASMA PHYSICS (June 2025 - Aug. 2025, seasonal position)

Los Alamos National Laboratory [LANL] (Los Alamos, NM)

• Integrated into an existing team to develop machine learning model components that classify astronomical transients and complete parameter estimation, with the ultimate goal of creating a foundation model for kilonovae

• Developed machine learning workflows compatible with existing data processing pipelines

• Implemented normalizing flow models using Pyro and Zuko in Python and combined them with existing transformer model components built in PyTorch

• Attended Zwicky Transient Facility (ZTF) Summer School 2025 hosted at the University of Minnesota, where I expanded my astrophysics understanding to improve machine learning model development

POST-BACHELORS STUDENT IN COMPUTATIONAL PHYSICS (Oct. 2022 - May 2024)

Los Alamos National Laboratory [LANL] (Los Alamos, NM)

• Implemented neural network sensitivity measures to analyze image-to-scalar regression models, with both python’s Tensorflow/Keras and Pytorch packages

• Developed and published python module to GitHub, including documentation and unit testing

• Implemented and trained Vision Transformer machine learning models for image-to-scalar regression

• Developed Vision Transformer tutorials and published on GitHub and in the Towards Data Science blog

• Presented machine learning research in talks and posters at conferences on Data Science, VVUQ, and High-Performance Computing

COMPUTATIONAL RESEARCH METHODS STUDENT (Feb. - Apr. 2023)

The Computational Research Access NEtwork [CRANE] (Virtual Seminar - https://www.cranephysics.org/)

• Completed five-week unit on implementing numerical methods in python, including Runge-Kutta, 1D finite difference, and fast fourier transforms

• Completed three-week unit on Monte-Carlo methods, which included implementing MC methods in python to simulate casino games and neutron transport

• Completed four-week unit on signal and image processing, which included writing python code to analyze Langmuir probe and plasma interferometer data

LOS ALAMOS DYNAMIC SUMMER SCHOOL [LADSS] (June - Aug. 2022, seasonal position)

Los Alamos National Lab (Los Alamos, NM)

• Analyzed reduced-order modeling methodologies for bolted connections in finite element software by comparing to a small-scale physical test

• Implemented a Bayesian Optimization algorithm to update finite element modeling parameters, which integrated a Python algorithm with calls to the finite element software ABAQUS

• Attended weekly lectures with hands-on components on topics such as signal processing, modeling dynamic systems, model validation, and more

DIRECTOR’S SUMMER PROGRAM [DSP] (May-Aug. 2021, seasonal position)

National Security Agency [NSA] (Fort Meade, MD)

• One of 21 participants chosen from 240 applicants nationwide

• Learned about convolutional neural networks and implemented and trained them for novel classification tasks

• Analyzed data from neural network classifiers to improve their performance

• Read unclassified and classified academic literature in unfamiliar subjects and applied the knowledge to my research project

• Presented research project findings to professional researchers at the Institutes for Defense Analysis (IDA) at Princeton Center for Communications Research (CCR)

• Prepared and delivered briefing to the Director of the National Security Agency on cryptanalytic techniques and results as a result of my research project

SECRETARY & FOUNDING MEMBER OF THE BUILT WORLD ENTERPRISE [BWE] (Jan. 2019-Dec. 2021)

Michigan Technological University [MTU]'s Enterprise Program (Houghton, MI)

• Developed innovative solutions to address existing problems in the field of civil aviation surface safety, and evaluated these solutions with a cross-disciplinary approach

• Integrated research in human factors, saliency, and situational awareness into a civil engineering foundation

• Gathered interdisciplinary feedback from aviation and human factors industry professionals

• Produced technical writing to describe research practices and results, to persuade for the implementation of innovative solutions, and to apply for external funding

• Documented current practices and knowledge of the executive board for future members to reference through the use of meeting minutes and a shared file system

• Lead workshops for undergraduate and graduate students on Reader Expectation Theory as a way to advance their technical writing