I’m a computer science student at the University of Montana, where I’m building a strong foundation in software engineering and AI systems. Before beginning my degree, I completed a full-stack development bootcamp that introduced me to the fundamentals of creating APIs and designing front-end interfaces.
Since then, I’ve gained experience working with Python, Java, and JavaScript and I enjoy applying these languages to projects involving open-source AI models, data analysis, and automation. My recent work explores how to develop and implement AI-powered backends to create useful, innovative, and practical tools. I’m currently expanding my skills through a machine learning and computer vision course with OpenCV.
I am also deeply interested in cloud architecture and DevOps. I use Docker to containerize applications - such as my TalkTrack demo - and am actively learning Kubernetes, AWS, and cloud infrastructure design through self-study. My next goal is to earn the AWS Certified Solutions Architect credential and continue developing a skill set that bridges AI development with scalable, production-ready systems.
I’m currently completing a Post-Baccalaureate in Computer Science at the University of Montana, maintaining a 4.0 GPA while studying algorithms, data structures, software engineering, and systems design. My coursework has deepened my understanding of computational problem-solving and clean, maintainable code architecture.
Prior to the program, I attended Montana Code School’s full-stack bootcamp, where I learned modern web development with JavaScript, React, Node.js, and RESTful APIs. Since then, I’ve continued expanding into Python, AI/ML, and cloud technologies through self-directed study and hands-on projects.
Professionally, I’ve worked as a Freelance Developer since 2024 — building production-ready applications and collaborating with creative agencies on client projects. Highlights include a Poker Trainer App with real-time hand analysis in React, and a CustomTkinter GUI controlling Arduino-based water-sampling hardware.
FastAPI backend that transcribes audio, performs speaker diarization, extracts key themes, and returns structured segment data for the TalkTrack plugin. Built with FastAPI, PyAnnote, Whisper, and Hugging Face Transformers.
AI-powered Adobe Premiere Pro plugin that automatically cuts, labels, and annotates interview footage using speaker diarization and topic analysis. Built with React (UXP) and integrated with a FastAPI backend.
Minimal Java CLI for 3x3 cube moves with colorized printing, history simplification, and solve-by-inversion. Demonstrates object-oriented programming and manipulating multidimensional arrays.
Collection of scrapers and visualizations to predict game outcomes based on statistical data from Sports Reference.