Engineering for hardware that has to work outside the lab
Embedded systems · Autonomous vehicles · Imaging · FPGA
I am a computer engineer working across embedded systems, autonomous vehicles, imaging and FPGA design. I take on the parts of a programme that sit between disciplines, where the model meets the power budget, where the flight stack meets the airframe, where the sensor meets the test data, and get them working on real hardware.
What I do
4 practice areasEmbedded & Edge AI
Most machine learning works fine on a workstation and falls apart on a battery-powered board. I take models the rest of the way: choosing an architecture that fits the silicon, quantising it until it meets the latency and power budget, and building the inference pipeline around it so it survives contact with real hardware.
View engagements →Airframe to autonomy, including the parts nobody wants to own.UAV & Robotics Systems
Whole-vehicle work rather than one slice of it: structures, propulsion, avionics, telemetry and autonomous behaviour, plus the fabrication to actually build the thing. I have taken vehicles from a requirement to a flying, tested prototype across electric, turbine and underwater propulsion.
View engagements →Characterise it, test it, and prove the numbers.Imaging & Sensor Systems
Image sensor and detector work: characterisation, bench bring-up, and the data infrastructure that turns raw test output into a decision. This is my day-to-day professional practice rather than research work, and it covers the unglamorous middle of a sensor programme where most schedule risk actually lives.
View engagements →Custom logic where a CPU will not do.FPGA & Reconfigurable Computing
FPGA design and hardware/software co-design for cases where timing, throughput or determinism rule out a general-purpose processor. Includes partial reconfiguration, where the fabric changes function at runtime rather than being fixed at build time.
View engagements →Selected work
7 case studiesReconfigurable CubeSat Clusters
A compute and communications stack that turns a swarm of 1U CubeSats into a single elastic cluster, with FPGA payloads that change function in orbit and workloads that migrate between satellites in seconds.
Read the case study →NASA MINDS 2025 - Exceptional Experimental DesignAir-and-Water Autonomous Vehicle
AQUAD: a single vehicle that flies to a site, submerges, manoeuvres underwater and returns to the air, on one charge. Built against a brief targeting ocean worlds such as Europa.
Read the case study →NASA MINDS 2024 - Honourable MentionWireless Power and Data Transfer
Paired resonant Tesla coils beaming power and low-frequency data across a gap with no conductor between them, and the electromagnetic compatibility engineering needed to keep nearby avionics alive.
Read the case study →NASA MINDS 2024 - FinalistAutonomous Aerial Docking and Recharge
A heavy-lift carrier UAV acting as an airborne charging hub and data relay, letting micro-drones dock in flight to recharge, offload sensor data and borrow GPU cycles.
Read the case study →Working together
Most of my work sits at a boundary: a model that has to fit a power budget, a flight stack that has to match an airframe, a sensor whose numbers have to survive production. Those handoffs are where schedules slip, and they are usually nobody specific's job.
If you have a problem shaped like that, tell me what you are trying to build and what is currently in the way.