I design and build robots end-to-end — from low-level microcontroller firmware to real-time computer vision running on the edge. Currently studying Robotics & AI at the University of Hertfordshire.
I specialise in embedded systems, computer vision, and autonomous robotics — bridging the gap between physical hardware and intelligent software. I'm comfortable across the full stack of a robot: writing real-time firmware in C, fusing sensor data, and deploying machine-learning models on resource-constrained hardware.
My projects span ROS 2 navigation and SLAM, custom-trained YOLOv8 object detection, face and gesture recognition with depth cameras, and offline voice recognition on microcontrollers. I care about systems that hold up in the real world — low-latency, on-device, and reliable.
Right now I'm exploring sensor fusion, probabilistic robotics, and ML deployment on the edge, and I'm open to internships, placements, and roles in robotics, autonomous systems, and AI engineering.
The stack I use to design, build, and deploy autonomous systems.
A selection of robotics and AI systems I've built. More on my GitHub.
An autonomous classroom assistant built on TurtleBot 4 (group project). Uses ROS 2 with SLAM and LiDAR for real-time mapping and autonomous navigation around a dynamic environment.
A custom-trained YOLOv8 detector deployed on a Raspberry Pi, classifying objects from a live video feed with on-device inference — practical experience in transfer learning and edge deployment.
Real-time face recognition using an OAK-D depth camera and DepthAI. Logs attendance with timestamps to Google Sheets with local CSV backups — sub-second identification, robust across lighting conditions.
Real-time hand-gesture classification (palm, thumbs-up, OK, point, wave) via MediaPipe 21-point landmarks and DepthAI, with a temporal buffer for motion gestures. 20+ FPS on edge hardware for touch-free control.
An autonomous maze-solving robot on a Raspberry Pi Pico. Uses an asynchronous finite-state machine for modular wall-following and turning, guided by three ultrasonic sensors. Built independently.
Wake-word detection running fully offline on an ESP32 using TensorFlow Lite Micro — speech recognition on a microcontroller with no cloud dependency.
A collection of bare-metal STM32 projects in C — real-time motor control, UART communication, and embedded systems fundamentals.
Real-time face detection on a Raspberry Pi AI camera with OpenCV, running fully on-device — optimised for low-latency inference, suited to access control and monitoring.
Reactive autonomous robots: an obstacle-avoidance platform using ultrasonic ranging and a proportional-control line follower on a Thymio robot — real-time control and hardware/software integration.
Teaching and web design, helping students build practical technical skills.
Supporting residents with daily care, monitoring vital signs, and maintaining health & safety standards — strong communication and teamwork under pressure.
One-to-one English tutoring with tailored lesson plans, improving students' proficiency and confidence.
Mechatronics, Robotics & Automation Engineering. Programming robots, computer vision, electronics, 3D design, and control theory.
Physics, Chemistry, Mathematics and Computer Science — foundations in programming and analytical problem-solving.
Open to robotics, AI and software roles, internships, and collaborative projects. The fastest way to reach me is email or LinkedIn.