I'm a third-year Applied Mathematics student at the University of New Hampshire, concentrating in Computational Mathematics and Machine Learning. I'm also a film maker, musician, poet, and tinkerer. In short, I'm a creative nerd who uses technology to create and build things that interest me. When I'm not working on my homelab, studying for exams, or DJing, you can usually find me lifting or outdoors enjoying this beautiful planet that we get to call home.
Contact: mlabrecque2002 [at] gmail (dot) com
(WIP)
I DJ for fun at my college radio station (91.3FM WUNH) and our specialty is we only play music which has not charted in the Top 40 on the Billboard Hot 100 charts. However there wasn't any easy way to determine if a song had charted or not. I solved this by writing a small Python program which automates the retrieval of Billboard data and allows someone to querry it for artist and song data.
A source-to-source compiler written in Python that translates Julia code into functionally equivalent MATLAB scripts. This project is ongoing as a final project under the guidance of Professor Melanie Vinning, this project originally started out as a joke due to both of us disliking MATLAB but turned into a full on project where I learned language design, parsing, and the challenges of cross-language translation.
I decided to put my design, engineering, and programming skills to the test by working on building a computer controlled telescope from scratch. The base of the project is using a custom gear assembly controlled by an Arduino microcontroller to adjust the telescope's position. The telescope also automatically accounts for the Earth's rotation as well as the latitude/longitude during positioning. Updates will be posted on YouTube.
Over the last year I've slowly built out a homelab which allows file hosting, machine learning, and self-hosting of my own personal projects. The homelab is powered by a Raspberry Pi 5 which is utilized as both a DNS for ad-blocking using PiHole as well as file hosting/sharing across all of my devices, and will soon also have a M5 Mac Mini which utilizes the Llama.CPP framework to run open-weight LLM models such as Gemma 4, as well as handling more beefy compiling needs for projects.