Current members of the Research Software Engineering team are listed below. Previous members of the team can be found on our Alumni page.

Paul Richmond

Paul is an EPSRC Research Software Engineering Fellow. Paul’s career as an academic researcher has always been focused on the development of software to support research, predominantly through the application of emerging hardware architectures to complex systems simulation. His technical expertise in GPU computing has led him to work more broadly, engaging with researchers in a wide range of domains to embed accelerated and GPU computing into their research ecosystems. His background in independent research means that he self-identifies as a Research Software Engineer with a strong emphasis on research relating to the application of GPUs. He is the director of the RSE group and oversees and manages team members and their more broad contribution to projects around research software development.

Bob Turner

Bob is a senior research software engineer who started his career in software and databases after completing a degree in Applied Physics at the University of Durham. After four years in the private sector, he did a PhD in Biophysics at the University of Leeds, before working as a postdoc researcher at the University of Sheffield in several departments, including Physics and Astronomy, Molecular Biology and Biotechnology Mechanical Engineering and the Dental School, reflecting an unusually broad range of research interests spanning microscopy, microbiology, engineering and healthcare.

An accomplished researcher with some important publications, as a software engineer Bob collaborates with researchers to develop and improve software. This of course involves writing code, but also lots of liaison, discussion, leadership and, most importantly, listening!

Bob’s role includes contributing to the management of the RSE team, under Paul Richmond’s leadership. His work includes:

  • Advising and helping researchers to implement good software engineering practises (e.g. testing, version control, documentation, reproducible execution, packaging, licensing)
  • Writing research software (e.g. in Python, MATLAB, R)
  • Training
  • Line management of five team members
  • Establishing new externally-funded collaborations
  • Advocating and acting to improve the standards of research software (e.g. running or delivering talks, communication via social media, engagement with university committees)


Robert Chisholm

Robert is a Research Software Engineer in the process of completing his PhD at the University of Sheffield. He specialises in GPU accelerated computing and complex system simulations, following his PhD’s focus on improving the performance of spatial communication in GPU accelerated algorithms.

He is currently working on the PRIMAGE project, which proposes an open cloud-based platform to support decision making in the clinical management of two paediatric cancers. In particular, wokring towards the development of a cell scale model of neuroblastoma to be scaled across multiple GPUs and distributed HPC resources.

He is also contributing towards the new version of FLAMEGPU software framework, facilitating wider access to complex systems modelling on GPUs.

Peter Heywood

Peter is a Research Software Engineer in the process of completing his PhD at the University of Sheffield. He specialises in GPU accelerated computing and complex system simulations; including transport network simulation and biological cellular simulations. He is currently working on the STriTuVaD project (a Horizon2020 project), which focuses on the use of in silico trials to support and improve tuberculosis vaccine development.

Twin Karmakharm

Twin is a Research Software Engineer who completed his PhD at the University of Sheffield. He specialises in High-performance agent-based pedestrian simulation, Parallel computing using GPUs, Virtual reality and Deep learning. He currently provides consultancy, training and technical support for researchers on Deep learning and other GPU related software engineering problems.

Matthew Leach

Matt is a Research Software Engineer in Complex Systems. He has a background in computer graphics, using physical-modelling to produce animations. He has recently completed his PhD on modelling the human mouth using the finite element method and also has experience with fluid simulation. Aside from physical-modelling, he also has research experience working with virtual and augmented reality.

Matt’s work on the team primarily revolves around the development of FLAMEGPU and advocating the use of GPU computing to support research. He is currently improving the performance of a model of tuberculosis spread.

  • Email: m.leach (at)
  • Github: @MILeach

Neil Shephard

Neil has taken a convoluted path to reach his current role as research software engineer. After completing his undergraduate (BSc Zoology and Genetics) and post-graduate (MSc in Genetic Epidemiology) at The University of Sheffield he spent a number of years as a Genetics Statistician researching the aetiology of complex human diseases learning UNIX system administration and literate programming along the way at University of Manchester, and University of Western Australia before returning to University of Sheffield. He then shifted careers to medical statistics and spent eight years working at the Clinical Trials Research Unit at the University of Sheffield. Throughout this time Neil developed and became enthusiastic about reproducible research and developed practical approaches to achieveing reproducible research in R using RMarkdown.

In 2018 he left academia for the private sector working for a telematics company using data captured from mobile phones and “black boxes” to quantify drivers behaviour. Here he developed an understanding of working with geo-spatial data and learnt Python along with various aspects of good software development practice and version control of software using Git.

Current projects:

Interests include:

  • Reproducible research and literate progrmaming
  • Python, R and Bash
  • Evolutionary Genetics
  • Emacs and Org-mode


Daniele Tartarini

Daniele joined the RSE team in 2020. He mainly supports:

  • CompBioMed2 Centre of Excellence for Biomedical Applications (EC-Horizon2020 project).
  • INSIGNEO Institute for in silico medicine.

In CompBioMed, he optimises biomedical applications and workflows to make them ready for the next generation exascale supercomputers (i.e. machines capable of computing 10^18 floating point operations/second) and Cloud-HPC. The pFIRE (Parallel Framework for Image Registration) is one of the applications under development in CompBioMed.

Daniele has a PhD in “Interdisciplinary Sciences and Technologies” and a Laurea cum Laude in “Information Systems Engineering”, from the Universita’ del Salento in Lecce, Italy. His expertise spans from parallel and distributed computing, GPU computing, bioinformatics, machine learning, and computational mechanics.

Before joining the RSE team, he worked as Research Associate on a range of multidisciplinary projects:

  • ERC Excellence Science “A high-fidelity isogeometric simulation methodology for fracture in porous media”, PI Prof. Rene’ de Borst. Dept. of Civil and Structural Engineering, University of Sheffield.
  • EPRSC IAA “Accelerating in silico cancer research with graphics processors”, PI Daniele Tartarini. Dept. Of Mechanical Engineering, University of Sheffield.
  • EC-Horizon2020 CHIC, “Computational Horizons in Cancer: Developing Meta- and Hyper-Multiscale Models and Repositories for In Silico Oncology”, PIs Prof Marco Viceconti, Dr DC Walker. Dept. Of Mechanical Engineering, University of Sheffield.
  • EPSRC, Automatic finite element code generation for GPU/parallel architectures. Dept. of Engineering, University of Cambridge.
  • Italian Ministry of Education, Development of a distributed virtual laboratory of bioinformatics in a Grid infrastructure. University of Salento in Lecce, Italy.
  • He has also provided consultancy for public administration and private companies.


David Wilby

Following a PhD in Physics & Biology at the University of Bristol employing HPC-based optical simulation techniques and postdoctoral research at Bristol and Lund Universities in behavioural experimentation and ray tracing simulation in sensory biology, David made the transition to research software engineering in 2019. He is experienced in Python and MATLAB, with developing interest also in the languages R and Go.

David’s interests in research software relate to: impact enhancement, reproducibility and sustainability, best practice and environmental and social responsibility.

He has been involved with projects in: python packaging, web dashboards for data visualisation, service containerisation, API development and data visualisation.

Other technologies that David has worked with are: Django, TensorFlow, Docker, Jupyter notebooks, Javascript & Google App Script.

Contact Us

For queries relating to collaborating with the RSE team on projects:

Information and access to JADE II and Bede.

Join our mailing list so as to be notified when we advertise talks and workshops by subscribing to this Google Group.

Queries regarding free research computing support/guidance should be raised via our Code clinic or directed to the University IT helpdesk.