I am currently a third year computer science student attending Rochester Institute of Technology. I plan on focusing my studies in the areas of artificial intelligence, machine learning, computer vision, and full stack application development. I have gained over 7 years of programming experience in multiple languages including Java, Python, JavaScript, C, C#, and C++. I have also worked heavily with frameworks and tools such as Node.js, Electron, OpenCV, Firebase, Flutter, Tensorflow, and more. Some of my completed and in development projects are listed below.
A simple yet powerful motion profile generator for FRC robots. It was created with customization in mind so that it could be used for many different types of robots. The app was released for other teams to download and use. Many teams have adopted PathPlanner for use with their software, leading to almost five thousand downloads across all platforms. It was originally created using Java and JavaFX but was later ported to Node.js and Electron. I have recently rewrote the application using FLutter. This version will be released on the Apple App Store and the Microsoft Store. The GitHub repository can be found here.
A mobile app for tracking the attendance of students on an FRC robotics team. Students can clock in and out, set reminders, manage their logged time, and compare themselves to the rest of the team through the leaderboard. It was written with Flutter and uses Firebase to handle authentication and store data. It is available for students to download on the Apple App Store and the Google Play Store.
A powerful Android app created for computer vision on an FRC robot, but is flexible enough to be used in other applications. It uses a custom version of OpenCV to allow for more camera functionality than what was available at the time. It has functionality for communication with a robot over USB or ethernet, MJPEG streaming, saving and loading profiles, and access for many different camera settings.
A web application for aggregating and displaying global results of the 2021 FRC competion. Official leaderboards were only supplied for individual groups of about 60 teams, but many desired to see their team's standings on a global leaderboard. This application uses a Firebase backend to scrape data from the official results, then calculate global standings and store this in a Firestore database. The frontend web app was created with flutter and is still usable here. The leaderboard was widely used by teams throughout the competition, with hundreds of daily users.