Jose L.
Salmeron

I have spent three decades doing two things simultaneously that most people do one at a time: leading large-scale AI deployments in industry, and producing scientific research that advances the field. The combination is not incidental — it is the point.

On the industry side, I have occupied C-level and principal scientist roles at global organisations — Capgemini, BBVA, and now a stealth AI startup — leading technical teams, securing funding and delivering systems that operate in production. I have been principal investigator on programmes funded up to €15 million, managing the full arc from architecture to deployment across healthcare, finance, energy and defence.

On the scientific side, I hold the Cátedra — Spain's highest professorial rank — at CUNEF Universidad, and I am consistently ranked among the Stanford top 2% of scientists globally. With an h-index of 39 and over 6,800 citations from researchers in twenty countries, my work in explainable AI, federated learning, quantum computing and causal machine learning is among the most cited in each field.

The interaction between those two tracks is what makes both better. Research grounded in real operational constraints is more useful. Industry guided by rigorous science is more trustworthy. Boards and research councils alike have come to value that combination.