Ana received an MSc in Biomedical Engineering and Biophysics in 2013 from the University of Lisbon in Portugal, followed by a PhD in Medical Physics in 2016 from University College London in the UK. Her research focused on image‑guided and adaptive radiotherapy, advanced dose‑measurement techniques, and the design and characterisation of new water‑equivalent plastics for clinical light‑ion beams.
Ana joined the Radiotherapy and Radiation Dosimetry Group at the National Physical Laboratory (NPL) in 2016, where she now leads research in measurement science, analytical and Monte Carlo modelling, and rigorous uncertainty quantification. Her work supports the safe introduction of advanced radiotherapy technologies, with a particular focus on proton therapy. She aims to ensure that measurement and modelling frameworks are robust, traceable, and clinically relevant.
Alongside her core research, Ana explores early applications of generative artificial intelligence (AI) to support model validation, data interpretation, and decision‑making in complex measurement systems. She is particularly interested in aligning modelling and measurement outputs with real clinical workflows and the needs of people working in safety‑critical and regulated environments.
Ana supervises several PhD and MSc students and holds an Honorary Research position at University College London in the Department of Medical Physics and Biomedical Engineering. She has served on a national committee contributing to the UK proton‑dosimetry code of practice, has authored more than 50 peer‑reviewed publications, and has been actively involved in organising the PPRIG Proton Therapy Physics workshop at NPL.
Ana’s research focuses on high‑fidelity measurement and modelling methods, including Monte Carlo simulation, analytical modelling, uncertainty quantification, and emerging AI‑enabled approaches. These are applied to new and evolving technologies in safety‑critical environments. Her primary focus is radiotherapy, but her interests also extend to broader challenges in energy systems, quantitative risk assessment, and regulated innovation, where reliable simulation, validation, and uncertainty management are essential for confident decision‑making and compliance.