// available for internships & opportunities
Mathematics and computer science student at New York University who creates to change, be it in the form of applied machine learning frameworks to solve real-world problems or theoretical papers to advance the scholarly field. Driven by curiosity, obsessed with craft.
01 — About
I'm Gavin Gong, a mathematics and computer science student with a genuine passion for building machine learning implementation that solves real problems. I started coding when I was five years old, writing ragged programs to increase Steve's jump height twofold, and never looked back. To this day, I continue to write real applications and constantly learn.
What drives me isn't just completing assignments — it's the itch to understand mathematically how things work and make them better. Whether it's an MLOps system or a hardware project, I dive in headfirst.
I'm actively looking for internships and co-op opportunities where I can contribute meaningfully, learn from experienced engineers, and grow fast. Check out my work below or on GitHub.
02 — Skills
Languages
Frameworks & Tools
Concepts
Agentic AI Workflow
Data & ML Libraries
Soft Skills
03 — Projects
Air Quality Dashboard
Built a kernel-based spatial-temporal LSTM to generate PM2.5 pollution levels across the city of Elizabeth, New Jersey
Hybrid Risk Management Model
Hybrid deep learning model combining CNNs and LSTMs for enhanced risk management, with architecture variations
More on GitHub →
Exploring more projects across systems, tooling, and experiments. All source code lives on GitHub — feel free to dig around.
04 — Papers
Paper Submission for the 2026 Mathematical Contest in Modeling; infer latent audience vote shares for a global competition using previous raw data, quantifying uncertainty in reconstructed votes with confidence measures
Propose a (SAM)-based pedestrian infrastructure segmentation workflow optimized for efficient processing of geospatial data