معرفی
Dr. Francisco Perez-Reche is a Reader in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been a faculty member since 2012. He is actively involved in research, teaching, and supervising PhD students. His work bridges applied mathematics, data science, and public health, with a focus on modeling infectious diseases and food safety risks.
His research interests include:
- Mathematical and computational modeling of infectious disease transmission
- Machine learning for source attribution in epidemiology
- Quantitative risk assessment using Monte Carlo simulations
- Network-based immunization strategies (e.g., explosive immunisation)
- Dose-response modeling for pathogens like E. coli O157 and Campylobacter
His recent publications reveal a strong focus on public health challenges, including the role of untested individuals in COVID-19 spread, post-COVID health outcomes like diabetes and mental illness, and the origins of zoonotic pathogens. He applies interdisciplinary methods combining statistics, machine learning, and mathematical physics to real-world health problems.
Dr. Perez-Reche has contributed to high-impact studies involving large datasets and collaborations with public health agencies across Europe. His work has been covered by major media outlets including The Times, BBC, and international science news platforms.
He teaches courses in mathematical methods, machine learning, and physics, and serves as Director of Undergraduate Pathways in Physics at Aberdeen. He is a member of the Aberdeen Group for the Mathematics of Infectious Diseases (AGMID) and the Centre for Bacteria in Health and Disease (CBHD).
