Two worlds, one way of thinking
My path started in academic research — a PhD on ethics and decision-making in multi-agent systems, at a time when those questions were still mostly theoretical. The years since have been spent putting that thinking to work across pharma, aerospace & defense, automotive and finance: sectors with very different constraints, but the same underlying need for systems that reason well and that people can actually trust. Today I lead teams as a manager at Capgemini, and what I bring to that role is less a set of techniques than a way of framing problems that both worlds taught me.
What I see across these industries today
The organizations I work with are past the question of whether AI matters to them. What they’re wrestling with now is how to adopt it in a way that survives contact with real operations: legacy systems, regulatory constraints, safety cases, and teams who need to trust a recommendation before acting on it. That’s precisely the gap between an elegant model and a system someone can rely on — and it’s the gap I’ve spent my career learning to close, from both sides.
Research, still
That interest hasn’t stayed behind in academia — it shows up in the projects I lead and, from time to time, in a publication or a patent. Have a look at Publications and Projects if you’d like to see where that thinking has gone.
I don’t share client data or confidential information here, and everything on these pages reflects my own views rather than those of Capgemini, my clients, or past organizations.