Hi I'm Henry
I turn messy information into reliable decisions.
I’m a builder and researcher working across AI, data, and markets. I combine research discipline, market experience, and long-term systems thinking to build dependable systems for high-stakes problems.
What I build
Data foundations
I turn messy, real-world data into dependable foundations for machine-learning and analytical systems.
Agentic systems
I turn reasoning-heavy workflows into reliable layers of agents, reusable skills, and deterministic automation.
Decision tools
I combine broad information, market data, and structured reasoning into decisions I can test and act on.
Selected projects
RSS3 blockchain data infra
At RSS3, I led blockchain data-platform and infrastructure work that cut cloud costs by 40%, moved ETL and indexing workloads from TypeScript to Go, and preserved portability across cloud providers.
Production · 40% lower cloud cost
RAMPVis public-health research
During my PhD, I became a D3.js expert by using it extensively for data visualization research. I also answered the Royal Society’s call to support COVID-19 analysis used in Scottish Government policy.
Research · 10+ publications · Named on £1M+ EPSRC grants · UK Global Talent
RSSHub open-source network
I’m a core contributor to RSSHub, an open-source RSS network with more than 40,000 GitHub stars and thousands of global instances.
Open Source · 40,000+ GitHub stars
How I think
Reason from first principles
I define the real constraint, test assumptions, and choose the simplest system that can carry the work. I think of it as disciplined laziness.
Extract signal from data
My research habits start broad: gather evidence from many sources, test it carefully, and narrow the data toward the insight that can change a decision.
Build for compounding
I have spent years turning repeated work into knowledge, automation, and feedback loops that become more useful over time. The long term is where small advantages compound.
Now
Markets have been my longest-running laboratory: I started trading on the day I turned 18. Today, I bring the research habits, data foundations, and automation systems above together in my own AI system for financial research and decision-making, applying it in a family-office context to structured products trading and wealth management.
Beyond the systems
My path has been nonlinear: I skipped the bachelor’s, completed an MSc in Computer Science with Distinction, and defended my PhD during COVID-19.
I read broadly through feeds I choose, self-host FreshRSS, contribute to RSSHub, and maintain an Obsidian knowledge base and my own information pipeline. I reject doomscrolling; Carrot, my cat, reminds me that not everything needs automating.
If you’re building AI systems that turn complex data into consequential decisions—especially in markets or data infrastructure—I’d like to compare notes.