• Head development of new products using AI-integrations to decrease friction between gym owners and their day-to-day operations.• Develop roadmap with founder and CEO of Wodify exploring new growth avenues.

• Engineered a Retrieval-Augmented Generation (RAG) model to extract pertinent information from patient health records, automating the drafting of insurance appeal letters using the GPT-4 API.• Modernized billing UI using React and TypeScript, resulting in a more intuitive user experience and a significant decrease in errors during patient registration, affecting over 200 million individuals with a record in Epic.• Led design sessions with key customers, including Mayo Clinic and Stanford Health, to gather requirements and understand end-user goals, incorporating feedback into final releases.

• Developed and trained convolutional neural network (CNN) from aerial LiDAR point cloud data to classify archaeological features in the Mayapan region using PyTorch.• Worked with domain experts to create prototype of GIS tooling to overlay AI predictions on LiDAR data from unexcavated sites, accelerating the discovery of archaeological ruins.• Lead and participate in weekly reading groups on the latest papers in the field of AI and deep learning.

• Highlighted sectors and regions poised for growth by creating a time-series forecast to model construction spending in five major metropolitan areas, leading to an expected 7.6% increase in annual revenue.• Co-authored report detailing expansion routes for Schuchart Construction using Pandas to analyze data pulled from employment, GDP, population, and migration datasets.• Utilized Tableau and Matplotlib to produce data visualizations displaying geographic areas and sectors with growth opportunities.

• Worked 20-30 hours/week during school to pay for college tuition.

• Awarded 1st place at the Colorado Science Symposium for contributions to the analysis of the impact of the invasive Rhinocyllus conicus species on the native Colorado thistle population.• Modeled the declining native thistle population using R as a method of predicting a future local extinction.• Improved population density estimates of the R. conicus species by identifying and correcting an error in sampling method.