Selected work

Projects that prove the skillset.

Each project below is written like a case study: problem, stack, outcome, and why it matters. That makes the site useful for bursaries, scholarship panels, internships, and competition judges.

Computer Vision Edge AI Robotics Embedded Systems Accessibility
Flagship project

JØ7 VIREO — Assistive vision platform

A wearable offline assistive system that uses a custom-trained YOLOv8m model to detect 100 everyday object classes, estimate distance, and provide audio feedback to visually impaired users.

  • Runs on edge hardware without cloud dependence.
  • Combines camera vision, distance awareness, and haptic safety feedback.
  • Built around low-cost hardware and reuse of repurposed lithium-ion batteries.
  • Designed for real-world navigation, privacy, and accessibility.
YOLOv8m Raspberry Pi Hailo LiDAR Audio feedback
Competition engineering

Cars4Mars African Rover Challenge

A rover systems project built through the Cars4Mars competition, combining 3D CAD, autonomous thinking, mechanical design, electronics, and programming under contest constraints.

  • Team Martian Mechanics won Best Design Award two years in a row.
  • Placed first this year and won the competition overall.
  • Demonstrates mechanical design, systems thinking, and reliable build execution.
  • Useful proof of practical engineering ability under pressure.
3D CAD Robotics Systems design Teamwork
ML pipeline work

Dataset annotation, training, and deployment

Work focused on the complete machine-learning lifecycle: collecting data, annotating it properly, training models, evaluating performance, and deploying on constrained devices.

  • Hands-on experience with data annotation workflows.
  • Model training and debugging in PyTorch.
  • Performance-focused deployment for edge hardware.
  • Built around speed, accuracy, and reliability tradeoffs.
PyTorch OpenCV Annotation Deployment
Technical growth area

Embedded AI and sensor fusion exploration

Ongoing work connecting sensors, control systems, and computer vision so that software decisions map to physical-world actions.

  • Raspberry Pi and ESP32 integration.
  • Arduino IoT programming and hardware interfacing.
  • PCB design and electronics prototyping.
  • Practical focus on portability and cost.
ESP32 IoT PCB design Sensors