Embedded Systems | ML for Aerospace | Spacecraft Telemetry
I'm a CS student in New Zealand obsessed with rockets and spacecraft. Currently teaching myself embedded C++ by building a rocket flight computer from scratch, and applying ML to real space problems through hackathons. Currently building embedded systems and ML solutions to tackle real-world aerospace challenges.
Implementing custom drivers and working directly with datasheets to learn low-level sensor integration.
Right now: Writing microsecond-accurate C++ drivers for ultrasonic landing radar and implementing safe hardware-level interfacing to bridge 5V sensors with 3.3V ESP32 logic.
Goal: real-time sensor fusion, physics simulation, and ML-based autonomous recovery to enable fully autonomous flight systems Stack: Embedded C++ • ESP-IDF v5.2 • ESP32-WROOM • Hardware Integration
ActInSpace New Zealand 2026 | Team Lead
Led a 4-person team to deliver an AI system that improves satellite collision decision-making
What I did: Team coordination, product direction, business model, final pitch
Tech stack: Python, PyTorch, TypeScript
NASA Space Apps New Zealand 2025 | 2nd Place | Team Lead
Led a 4-person team to create an ML pipeline that turns telescope data into actionable 3D visual insights
What I worked on: ML pipeline design, Random Forest training, habitability prediction, task allocation
Tech: Python, scikit-learn, Flask, Three.js, Docker
Building functional embedded systems and ML projects while pursuing CS studies, turning ideas into tangible solutions