About Me
I’m a software developer, researcher, musician, and lifelong learner with a love for computing, math, and more! From conducting undergraduate research to studying abroad in Seoul, South Korea, I've always pushed myself to try new experiences. Now, I am pursuing a master's degree in Computer Science at the University of Florida. My main computing interests are machine learning, reinforcement learning, and software engineering.
View my Résumé 
Study BlogEducation
University of North Florida
Jacksonville, FL
B.S. in Computing and Information Sciences – Computer Science
College of Computing, Engineering & Construction
Minor: Mathematics, International Business
GPA: 3.99 / 4.0
Graduated summa cum laude; Member of Hicks Honors College
Skills
Python
Java
C Language
HTML
CSS
PyTorch
Assembly
Unix
GitProjects
Technologies Used
- Python
- PyTorch
- Ray RLlib (Legacy API)
- PettingZoo (Gymnasium)
- MAPPO Algorithm
- Inspired by this MATLAB area coverage example
Multi-Robot Exploration with Deep Reinforcement Learning
This work presents a Deep Reinforcement Learning (DRL) framework for coordinating a team of robots to explore an unknown grid-world environment while maintaining a connected communication network. The proposed system adapts a multi-agent actor-critic algorithm (MAPPO) using Ray RLlib’s legacy API and PettingZoo (Gymnasium) for environment modeling. Inspired by a MATLAB-based area coverage example, this project extends the task to include communication constraints by modifying the reward function. Empirical results demonstrate that the learned policy achieves moderate to high success rates in exploration while preserving network connectivity, and shows potential for generalization to larger teams.
(GitHub link coming soon)
Technologies Used
- FastAPI (Python)
- Next.js / React (TypeScript)
- TailwindCSS
- Vercel / V0
- GitHub (Team Collaboration)
- External APIs for images, text, and Google Flights
Aeroatlas Travel Planner – Audience Choice Award Winner
We developed a travel itinerary planner that generates custom trip plans with activities, images, and local insights based on user input. The project was awarded the Audience Choice Award at the School of Computing Symposium at UNF. As part of a five-person team, I focused on developing the dynamic itinerary page, integrating a FastAPI backend with several APIs to fetch images (flags, attraction previews), trip descriptions, and user-saved itinerary data. Users can add restaurants, attractions, hotels, and custom items to their itinerary, manage a packing list, and view flight information via Google Flights. All changes persist on the backend to support a fully interactive experience.
(GitHub link coming soon)
Technologies Used
- Java
- JavaFX & CSS (GUI Development)
- Linux
- SSHJ - SSHv2 library for Java
Raspberry Pi Interface
This project implements a desktop interface in Java to control a Raspberry Pi system. It features a graphical UI to interact with the Pi’s components and monitor key system resources. Key modules include a file manager for uploading, downloading, renaming, and deleting files; a basic shell interface; and real-time CPU, RAM, disk usage monitoring, and a GPIO control panel (currently read-only). The application makes use of JavaFX Tasks to handle multithreaded operations, ensuring background processes such as loading and data collection do not block program usage. Users can save their system preferences for greater convenience when re-launching the application.
View on GitHub