Professor Biagio Lucini

Personal Chair, Mathematics

Telephone number

+44 (0) 1792 602284

Email address

Office - 338
Third Floor
Computational Foundry
Bay Campus
Available For Postgraduate Supervision


Professor Lucini is a current Royal Society Wolfson Merit Awardee with interests spanning across Mathematics, Physics and Computer Science. In his research, he combines the use of High-Performance Computing and Advanced Mathematical Algorithms in order to address open problems in Particle Physics, such as the description of fundamental interactions beyond the currently known four forces of nature in order to explain the inner nature of the Higgs boson and the existence of Dark Matter.

A Ph.D. graduate from Scuola Normale Superiore (Pisa, Italy), Professor Lucini joined Swansea University in 2005, after having been a Postdoctoral Fellow at Oxford University (2000 – 2003) and at ETH Zurich (2003 – 2005). In 2011, he became Professor at Swansea, where he has been the Director of the Mathematics Department from 2015 to 2020. In 2018, he was elected Fellow of the Learned Society of Wales. In 2020 he has been awarded a Leverhulme Research Fellowship to investigate Machine Learning applications in Statistical Mechanics and in Quantum Field Theory.

Professor Lucini is the Director of the Swansea Academy of Advanced Computing, the Technical Director of the UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing and a member of the Technical Directorate of the STFC DiRAC High-Performance Computing facility.

Areas Of Expertise

  • Numerical Methods and Algorithms
  • Theoretical Particle Physics
  • Lattice Gauge Theories
  • Strongly interacting systems
  • Critical Phenomena
  • Monte Carlo Algorithms
  • Machine Learning
  • High-Performance Computing

Career Highlights


Professor Lucini is primarily an Applied and Computational Mathematician. His main field of research is Particle Physics, but he has also an interest in Statistical Mechanics, Strongly Correlated Electrons, applications of Machine Learning, Numerical Algorithms, Monte Carlo Methods and High-Performance Computing.


He specialises in numerical calculations using Monte Carlo Methods in Strongly Interacting Gauge Theories and in Statistical Mechanics running on state of the art supercomputers, for which he develops efficient parallel code. In relation to the latter activity, he has led the development of a specialised High-Performance Computing benchmark, BSMBench, which has been adopted by leading companies in the supercomputing market segment.


A full, constantly updated list of his publications can be found on Inspire. His research work is also reported in his Inspire Author Page and in his Google Scholar entry.

Award Highlights Collaborations