Marcelo Pereyra

Marcelo Pereyra is a Professor in Statistics at the School of Mathematical & Computer Sciences of Heriot-Watt University and the Maxwell Institute for Mathematical Sciences in Edinburgh, UK. His academic journey began with a double M.Eng. degree from ITBA (Argentina) and INSA Toulouse (France), followed by a M.Sc. from INSA Toulouse in 2009. He earned his Ph.D. in Signal Processing from the University of Toulouse in 2012, after which he served as a Research Fellow in Statistics at the University of Bristol from 2012 to 2016. In 2017, he joined Heriot-Watt University as an Assistant Professor in Statistics, was promoted to Associate Professor in 2019, and subsequently to Professor in Statistics in 2023.

His educational background includes:

• Ph.D. in Signal Processing, University of Toulouse (2012)
• M.Eng. (double degree) from ITBA (Argentina) and INSA Toulouse (France), with M.Sc. from INSA Toulouse (2009)

Professor Pereyra's research advances the statistical foundations of quantitative and scientific imaging. He has made important contributions to Bayesian imaging sciences and developed significant connections between statistical, variational, and machine learning approaches to imaging. His specific interests include robust uncertainty quantification in imaging inverse problems, automatic calibration and verification of statistical image models, scalable Bayesian computation algorithms derived from stochastic diffusion processes, and applications of imaging with high social or environmental value. His work sits at the intersection of statistics, computational mathematics, and imaging science, with a strong emphasis on developing mathematically rigorous methods that provide reliable uncertainty quantification alongside point estimates.

His recent publications demonstrate a clear trajectory toward integrating modern machine learning techniques, particularly diffusion models and generative approaches, with traditional Bayesian statistical methods for imaging problems. The research spans applications from medical imaging to astronomical observations and industrial inspection, with consistent emphasis on uncertainty quantification. His work increasingly focuses on developing scalable computational methods that can handle the high-dimensional nature of modern imaging problems while maintaining statistical rigor.

Professor Pereyra has received numerous prestigious awards throughout his career:

• SIAM SIGEST Award in Imaging Sciences for contributions to proximal Markov chain Monte Carlo methodology
• Marie Curie Intra-European Fellowship for Career Development (2013)
• Brunel Postdoctoral Research Fellowship in Statistics (2012)
• Postdoctoral Research Fellowship from French Ministry of Defence (2012)
• Leopold Escande PhD Thesis award from the University of Toulouse (2012)
• INFOTEL R&D award from the Association of Engineers of INSA Toulouse (2009)
• ITBA R&D award from the Buenos Aires Institute of Technology (2007)

Professor Pereyra is deeply committed to developing early career talent, currently supervising five PhD students and two Postdoctoral Research Associates (PDRAs), having previously supervised four PhD students and three PDRAs to completion. His research has received significant support from Heriot-Watt University and the UK Engineering and Physical Sciences Research Council (EPSRC). He is known for fostering multidisciplinary collaboration, having organized eleven international interdisciplinary research meetings in the UK since 2012 and chaired the IMA Conference on Inverse Problems in Edinburgh (2022).

As a leader in his field, Professor Pereyra has held Invited Professor positions at prestigious institutions including Institut Henri Poincaré (Paris, 2019), Ecole Normale Supérieure Lyon (2023), and Université Paris Cité (2024). He frequently delivers invited talks at leading mathematical centers worldwide (CIRM, BIRS, IHP, Flatiron, Hausdorff School, INI, and ICMS) to promote multidisciplinary collaboration in imaging sciences.