About

I am an associate professor with a range of teaching and research responsibilities across Mathematics and Computing. I teach on several undergraduate and Master's modules, including supervising final-year student projects and also Master's students. My research background is in experimental high-energy nuclear physics, which involves smashing together nuclei at very high energies to recreate, on a much smaller scale, the conditions in the first few microseconds after the Big Bang. This research involves collecting and analysing several petabytes of data, so I am interested in advanced techniques for handling these data and working with colleagues in computing and data science on this. The synergies on the data analysis side with machine learning and so-called explainability are a recent focus. I have an interest in the connection between the distributions of the particles produced in the collisions and the mathematics describing non-equilibrium processes. I supervise PhD students working in these areas and work to infuse this research into my teaching.

Research interests

High-energy nuclear collisions at the CERN Large Hadron Collider.

By studying these collisions, we can learn about 'QCD' (Quantum Chromodynamics) the force that binds together the familiar matter we see around us. As a result of the collision, an extremely hot droplet of fluid is formed with remarkable properties. Many thousands of particles are created in each collision when this fluid 'freezes out'.  This research involves collecting and analysing several petabytes of data, so I am interested in advanced techniques for handling these data and working with colleagues in the Data Science Research Centre and School of Computing on this. I have an interest in the mathematical connection between the distributions of the particles produced in the collisions and the mathematics describing non-equilibrium processes.

I recently (2021-2023) led a group of international collaborators in the preparation and analysis of data from the A Large Ion Collider Experiment (ALICE) at CERN, relating, in particular, the measurements of strange particles. I am interested in supervising PhD or MPhil students on projects involving this and other topics at the interface of data science and physics. Please contact me for details.

Recent publications

The full list of the ~600 publications that I have as a member of the ALICE, STAR and NA49 Collaborations are available on the INSPIRE website. Some highlights include:

• Multiplicity dependence of (anti-)deuteron production in pp collisions at √s = 7 TeV (ALICE Collaboration) Phys. Lett. B794 (2019) 50-63
  
• Longitudinal asymmetry and its effect on pseudorapidity distributions in Pb-Pb collisions at √s_NN = 2.76 TeV (ALICE Collaboration) Phys. Lett. B781 (2018) 2-32
  
• Production of ⁴He and ⁴H̅e̅ in Pb-Pb Collisions at √s_NN = 2.76 TeV (ALICE Collaboration) Nucl.Phys. A971 (2018) 1-20
• Enhanced production of multi-strange hadrons in high-multiplicity proton–proton collisions (ALICE Collaboration) Nature Phys. 13, 535-530 (2017)
• Multi-strange baryon production in p-Pb collisions at √s_NN = 5.02 TeV J. Adam et al. (ALICE Collaboration) Phys. Lett. B, 758, 389 (2016)
• Centrality dependence of the charged-particle multiplicity density at mid- rapidity in Pb-Pb collisions at √s_NN = 5.02 TeV J. Adam et al. (ALICE Collaboration) Phys. Rev. Lett. 116 222302 (2016)
• Centrality evolution of the charged-particle pseudorapidity density over a broad pseudorapidity range in Pb-Pb collisions at √s_NN = 2.76 Tev J. Adam et al. (ALICE Collaboration) Phys. Lett. B 754, 373 (2016)
• Precision measurement of the mass difference between light nuclei and anti- nuclei J. Adam et al. (ALICE Collaboration) Nature Phys. 11, no. 10, 811 (2015)
• K⁰_S and Λ production in Pb-Pb collisions at √s_NN = 2.76 TeV B. B. Abelev et al. (ALICE Collaboration) Phys. Rev. Lett. 111, 222301 (2013)

All the above are open access.

Membership of professional bodies

• Member, Institute of Physics (MInstP) 
• Fellow, Royal Statistical Society (2019-2021)

Professional interests

I am the lead for the university's data science theme cluster Collaborative and Data-centric Engineering. This interdisciplinary group collaborates on the use of data science, including machine learning and artificial intelligence in modelling engineering products and processes.

Qualifications

Postgraduate

• Ph.D. in Nuclear Physics, Birmingham (1999)

Undergraduate

• B.Sc. in Physics, Manchester (1995)

Recent conferences

• Exotic Hadron Spectroscopy, York, 2019
• Institute of Physics Nuclear Physics Conference, Paisley, 2018 
• International Workshop on Exotic Atoms and Related Topics, Vienna, 2017
• Institute of Physics Nuclear Physics Conference, Liverpool, 2016
• Prospects in the Physics of Discrete Symmetries, London, 2014

International experience

Throughout my research career, I have had international collaborators and experience working abroad. In 2015 I spent one year based at CERN (European Particle Physics Laboratory) as a Scientific Associate (a kind of visiting scientist) as part of my work with the ALICE Collaboration, which I joined in 2008. I had previously carried out research, since 1999, with the STAR Collaboration based at Brookhaven National Laboratory in the USA, spending the first four years of my postdoctoral career living there on Long Island, NY. My thesis work was performed at CERN with the NA49 experiment and my first visit there in 1995 was my first ever flight! Since joining Derby (2016) I have continued my collaboration with CERN and also served as an external examiner for a PhD viva at the University of Turin (2018).

Teaching responsibilities

• Module Leader
  • Mathematical Modelling
  • Statistical Methods 2
  • Statistical Techniques (MSc Big Data Analytics)
• Project Supervisor
  • Research Methods and Independent Study in Mathematics
  • Independent Scholarship (MSc Big Data Analytics)

Additional interests and activities

I have long cycled as part of my commute and when this part of my daily routine stopped during the COVID-19 lockdown I discovered the joys of cycling for leisure. I have found many routes out into the Cotswolds and other rural locations near to my home town.