I'm a Swiss Army knife of software development with professional experience in developing virtual reality games, full-stack development, and teaching.
I have a strong background in machine learning which goes along with my data-driven approach to development to create the best product for the client and users.
When I'm not programming, I like to lift weights, go on runs, and listen to 80's music! I'm a sports analytics nerd to make up for my horrible predictions.
May 2025 - Present
I'm a full-stack engineer across 3 production applications that include a customer booking app, a vendor management portal, and an admin CRM. I designed and built cross-platform systems including a real-time messaging system deployed on AWS, an automated Stripe vendor payout system, and various full-stack features across Go microservices and React frontends.
Oct. 2024 - May 2025
I redesigned both the machine-learning pipeline on the backend and the UI/UX flow of the frontend. I created a FastAPI microservice which was able to speed up batch predictions by 200%. On the frontend I was able to clean up many views by utilizing data tables and frontend validation to create a more enjoyable experience for end-users.
Lehigh University
Sep. 2024 - May 2025
I maintained and enhanced the Lehigh TRAC program's Flask web-application by expanding admin tools to reduce the amount of manual database work. I also helped both Lehigh students and faculty with weekly VR workshops for classroom and community activities.
May 2023 - Aug. 2024
I was a part of the development of 14 multiplayer Unity VR lab experiences for two Utah Tech courses. In addition to building many small interactive systems, I optimized core network systems, such as making a render-texture sync system over 200% faster, so that students can save their progress on their labs and share their work with other students.
I taught a 9-week full-stack development summer program covering Vue, Express, MongoDB, and REST APIs to 19 students along side one other instructor. I guided 6 groups through the full-stack development lifecycle, advising on API design, feature scoping, and (a lot) of debugging.
Fine-tuned DistilBERT end-to-end classifer with chunked attention for media bias classification. Wrapped the model around a Next.js product while using LLM for label enhancement and storing results on Supabase.
Research project that utilizes principal component analysis to explore Southern Utah water trends and measure feature importance.
This is a fun project that aims to view lyrics via the lens of a text classification model. I'm experimenting with TF-IDF to classify songs into a genere via the lyrics of the song.