Samuel Pinilla

I am a research scientist at the Rutherford Appleton Laboratory RAL, working at the Harwell Science and Innovation Campus, (Didcot, UK).

I combine backgrounds in Computer Science, Mathematics and Engineering with AI for Science experience, moving with ease from abstract mathematical theory to algorithms for real-world applications. My work lies at the intersection of signal processing and machine learning. I am particularly interested in the theory of optimization and inverse problems with applications in science and engineering.

I drive solutions at the intersection of Theoretical AI, Hands-on Coding, and Applied Machine Learning, bridging theory and real-world impact to transform advanced AI theory into systems that perform reliably and produce measurable results. I move from mathematical AI theory → building robust AI systems → delivering results in production.

As a researcher, I have expertise in advanced optimisation, invexity, signal processing, optics, and explainable deep learning, with publications in NeurIPS, ICLR, Science Advances, Optica, ICASSP, and Nature Machine Intelligence.