About Me
I’m a systems engineer based in Buckinghamshire, UK, working at the intersection of distributed infrastructure and machine learning.
I have 20 years experience designing and building production platforms across FinTech, logistics, and EV infrastructure. Most recently, I served as Tech Lead at CrowdCharge, where I lead development a SaaS platform for optimising EV charging for businesses and consumers.
I’m almost at the end of an MSc in Software Engineering at the University of Oxford, where I focused on formal methods and machine learning. My thesis explored large-scale EV charging coordination under dynamic pricing and infrastructure constraints.
My work now centres on applying machine learning and optimisation techniques to real-world systems — particularly energy and infrastructure problems.
What I do
I design and build intelligent systems that operate under real-world constraints.
That includes:
- Architecting distributed, event-driven platforms
- Designing scalable data models and high-throughput ingestion systems
- Building simulation environments for complex physical systems
- Developing reinforcement learning environments for optimisation problems
- Training and evaluating neural network models
I’m particularly interested in:
- Reinforcement learning & Large action-space decision problems
- Energy systems & infrastructure modelling
- Forecast-driven control systems
- Bridging formal modelling with ML-based optimisation
Selected Projects
Some projects I’m particularly proud of:
EV Charging & IoT platform
Designed and built a distributed IoT platform to ingest and process large volumes of telemetry data from electric vehicles and chargers.
Reinforcement learning environment for EV coordination
Developed a scalable RL environment, modelling group EV charging under dynamic tariffs, carbon and grid constraints.
Simulation DSL for EV Infrastructure
Created a domain-specific language to generate simulations of electric vehicle and charger operations.
Distributed FinTech Platform
Engineered a high-performance, distributed low-code platform to reduce time-to-market for banking applications.
Technical Background
I work comfortably across the stack, but my strength lies in system design and architecture.
Languages I regularly use:
- Kotlin/Java
- Go
- Python
- TypeScript
Recently exploring:
- Rust
- Elixir
I’ve worked extensively with infrastructure-as-code (Terraform, CDK), event-driven systems (Kafka), and high-scale database design.
What I’m Moving Towards
I’m focused on roles where machine learning meets real-world systems — particularly optimisation, energy infrastructure, and decision-making under uncertainty.
Outside Work
I run, box and practice Brazilian Jiu Jitsu. I’m extremely average at running and boxing, and pretty terrible at BJJ.