Two decades in computational biology, multi-omics and clinical bioinformatics — from wet lab to production-grade pipelines. Applied AI is the newest layer on top of that domain depth: I bring it in where it genuinely helps teams move from prototype to real-world impact — not as a buzzword.
I help you decide which AI is worth implementing — with what data and at what risk — and which to avoid. No demos for the demo's sake.
Practical AI training, use-case spotting, safe automation of routine tasks, and support for clinical research.
Literature & evidence, grants, multi-omics, biomarkers, reproducible pipelines, and pilots on real data.
Roadmaps, risk assessment, pilot prioritisation, cross-team training, and a bridge between clinical and technical teams.
Concrete, time-boxed, each with a deliverable your team keeps — built from the consulting and training below.
For clinical and research teams who want to use AI on their real work.
Outcome: your team using AI on real tasks from Monday.
See details ↓For a service, unit or research group deciding where to start.
Outcome: a clear, realistic plan of where AI is worth it — and where it isn't.
Scope a sprint →For teams ready to build something real on their data.
Outcome: a working, validated pilot — from prototype toward production.
Start a pilot →Whichever engagement you start with, the work runs in one of two modes. Same foundation, two services: two decades bridging biology, clinical context and engineering — now pointed at where applied AI actually creates value in health R&D.
Independent, hands-on, scoped to a clear deliverable — not an open-ended retainer. Most engagements leave a written technical reference your team keeps.
Scope an engagement →For clinicians, managers and researchers who want to use AI on their own data and work — not just hear about it. I teach what I've shipped, not theory from a lab.
Discuss a session →A half-day, hands-on introduction to the AI tools available today — what they're good for, what they're not, and how to use them on the real tasks you face: searching and synthesising literature, drafting, structuring information, making sense of your data, and building simple automations for the repetitive tasks that eat your time. No code and no hype — you work with the tools directly and leave able to use them from Monday. Tailored to your team and delivered on request; if it fits a need, let's talk.
Clinicians & researchers — no coding required.
Half day · hands-on · adaptable to a master's module.
The right AI tools for your work — and a few automations to save time.
I bridge computational biology with modern AI to solve real problems in drug discovery and precision medicine. Beautiful algorithms fail without clinical context or scalability; simple pipelines win when they solve the right problem.
The best work happens at the intersection of disciplines: listening to domain specialists and translating their knowledge into technology — and, increasingly, helping those specialists wield AI themselves. I don't just analyze data; I take work from research prototype to something that runs in the real world, under regulatory constraints when needed.
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