CS @ University of Florida | Prev. @ NVIDIA
MY THREE.JS
PORTFOLIO
Hello, my name is Daniel Park. I am a fourth year Computer Science major with
a minor in Digital Arts and Sciences at the University of Florida (go gators!). I have
experience building and operating production software systems through internships
at NVIDIA and Northrop Grumman, where I worked on autonomous vehicle platforms,
perception tooling, and large scale infrastructure under real world constraints.
Outside of systems and backend work, I am deeply interested in front end
development and creative technology. I spend my free time exploring music
production, game development, and 3D art and rendering, and I am currently
working toward releasing a full solo game titled Tales of Wistaria. I enjoy
projects that sit at the intersection of engineering and creativity, where
technical rigor and expressive design come together.
Here are some of the projects I’ve worked on or am currently building. These range from production-style infrastructure systems to data-driven and machine learning applications, and reflect my interests in reliability, scale, and end-to-end system design.
Atlas is a production-grade infrastructure project focused on service orchestration and reliability. It manages a fleet of Linux nodes with a Go-based control plane, coordinating configuration propagation, rolling restarts, and traffic routing. The system is instrumented with Prometheus and uses MySQL and Redis for state management to simulate real production behavior under load and failure scenarios.
Ledger is a full-stack personal finance application that ingests and encrypts transaction data to generate actionable financial insights. It includes a rule-based categorization engine, cash flow analytics, and goal-based forecasting, all surfaced through an interactive Flask and React dashboard backed by PostgreSQL.
Spotistats is a machine learning driven music analytics and recommendation platform. It processes large-scale Spotify user data to train a convolutional neural network for personalized recommendations, and exposes results through backend APIs and a React frontend. The project emphasizes data pipelines, model evaluation, and low-latency inference.
Looking ahead, I want to push this project beyond exploration and into something more production ready and expressive. My next steps include building reusable animation and shader components, improving scene performance through better state management and render optimization, and introducing more intentional interaction design rather than purely decorative motion.
I am also interested in deepening my work with Three.js and GLSL by experimenting with custom lighting models, procedural geometry, and time driven shader effects that respond to user input or audio. On the frontend side, I plan to refine the architecture of the codebase by modularizing animation logic, tightening CSS structure, and improving accessibility and responsiveness across devices.
More broadly, this project serves as a foundation for future creative work where engineering and visual storytelling intersect. I aim to continue developing interactive experiences that feel polished, intentional, and technically grounded, whether that is through immersive websites, game prototypes, or real time visual systems.
Feel free to explore my repositories and reach out through my LinkedIn! I'm always looking for opportunities to grow as a developer.
Credits to Andrew Woan's youtube tutorial on gsap timelines and three.js