Alden Cutler

As part of a research project with my university, WPI, I spent the summer of 2024 in Lyon, France researching the public transit system. My team and I collected on the public transit system in Lyon and used it to produce a report on the system's efficiency and effectiveness. We developed visualizations of the data collected. All the code used to visualize the data is written in Python and is available on my GitHub page.

As part of the project, I created an interactive map of the city of Lyon. The city is divided into 59 "IRIS" zones, which are used by the French government to collect demographic data. Each zone represents an area with an average population of 2000 people, and is color-coded based on the ratio of wheelchair-accessible transit stops to total transit stops in the zone. This map is also available here.

Another map I created as part of the project shows where outages have occurred in the Lyon public transit system, overlayed on top of the metro lines. From this visualization, we can see that outages are more common at the intersections of metro lines and at stops which are also regional train stops. This map is available here.

ChordStorm is a web app made for GoatHacks 2024 that recommends music based on the current weather and your listening history. The app was built using Flask for the backend, OpenAI's GPT API for the music recommendations, and Spotify's API for the user's listening history. If you'd like to see the code, you can find it on my GitHub. We're working on a way to deploy the app so that it can be used by anyone, but for now, there is a demo video on the Devpost page. If you have an OpenAI API key, you can also clone the repo and run the app locally.

I'm a long-time fan of the game Minesweeper so while I was bored over my school break, I decided to make my own version of the game. I used Python and the Pygame library to make a complete re-creation of the game, including chording. If you'd like to see the code, you can find it on my GitHub.

While I was home from school for the summer, I came across a YouTube video describing how to create a neural network from scratch using only Python and Numpy (no TensorFlow or SciKit-Learn). I decided to give it a try and ended up creating a neural network that could classify handwritten digits with around 85% accuracy on the MNIST dataset. If you'd like to see the code, you can find it here.

This past December (2023), I participated in my first Advent of Code. I was introduced to the event by my Algorithms and Data Structures professor and decided to give it a try. I used a combination of Python and C to solve the problems. If you'd like to see the code, you can find it on my GitHub.