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.

Will Furnass

Will is a Research Software Engineer who is currently:

  • Helping Paul Richmond lead the RSE team
  • Contributing to the development and maintenance of University research computing platforms (inc. HPC)

Previous projects:

The path to this point has not been particularly direct: he has a computer science degree, has worked as a IT systems engineer in the film industry, has a PhD plus post-doc experience in water engineering (where he developed semi-physical and data-driven models of water quality in water distribution networks) and has provided support to the users of the University of Sheffield’s high-performance computing clusters. In addition he has taught or helped run RSE, water engineering and study skills workshops. His interests include helping researchers optimise data analysis workflows (primarily using higher-level languages), providing training in RSE best practices and systems administration.

He is an accredited Carpentries instructor and has facilitated Software and Data Carpentry workshops on topics including Python, R, version control with Git, the UNIX shell and SQL.

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.


John Charlton

John is a current PhD student and Research Software Engineer. Previous work has involved simulating dense crowds of virtual pedestrians, using GPUs to model many tens of thousands of people in real time. His interested include agent-based modelling, visualisation and interaction of simulations. Expertise includes GPU-accelerated computing and agent-based modelling approaches.

He is currently working on a RateSetter project examining the boarding rate and risk at the Platform-Train interface.

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.

David Jones

David is a Research Software Engineer in the University of Sheffield’s RSE group.

David graduated from the University of Cambridge with a degree in mathematics and a Post-Graduate Diploma in Computer Science, and has since taken a variety of mostly systems programming roles in industry before recently being employed in The Academy.

David has expertise in C, Python, Go, Lua, embedded microcontrollers, programming language runtimes, Software Engineering Management, /bin/awk, and the PNG image format.

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.

Anna Krystalli

Anna is a Research Software Engineer. She fell in love with statistical programming and R in particular, during her PhD in Macroecology at the University of Sheffield. This was followed by two years of freelancing as a Research Data Scientist. These and previous experiences as a quality assurance auditor have led her to focus on efforts to promote more transparent, robust, reproducible research through better scientific software development and research data management.

She’s also passionate about community and capacity building. She has extensive teaching experience, was part of the inaugural Mozilla Science Lab Open Leadership Training cohort, has been a veteran mentor on following rounds and a member of the organising committee for the Sheffield R users group.

Key interests include:

  • All things #rstats
  • Reproducible research
  • Open source research technologies and culture enabling next generation open science.

  • Email: a.krystalli (at)
  • Twitter: @annakrystalli

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

Bob Turner

Bob is a 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 codes in Python, R and Matlab using version control with git and applying good software engineering practices such as documentation, automated testing and continuous integration. He enjoys working with a diverse range of collaborators in different disciplines. Current and recent work includes:

  • Porting code for identification of the polar sea ice edge from Matlab to Python and deploying this using Docker.
  • Documenting and developing GPy, a Gaussian Process based machine learning framework for Python.
  • Reviewing research software and developing formal processes for this.
  • Leading a software engineering team building epidemiological modelling software (Python) as part of the Royal Society’s Rapid Assistance in Modelling the Pandemic initiative.
  • Supporting RedCAP database infrastructure (using Vagrant and Ansible) for clinical trials in collaboration with INSIGNEO, the Biomedical Research Centre and the Hallamshire Hospital.
  • Delivering training on reproducible research, version control, Python and R.


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.

Fariba Yousefi

Fariba Yousefi is in the process of completing her PhD in Machine Learning at the department of Computer Science, University of Sheffield. She recently joined the research software engineering team as a machine learning research engineer at the university of Sheffield.

Her research interests are Gaussian Processes, data scarcity, imbalanced data and multi-task learning. She enjoys working on healthcare applications.

Fariba’s experience in chairing and organizing scientific events include: the Gaussian processes summer school ( and the Women in Machine Learning (WiML, where she was the senior programme chair at the affinity workshop for ICML 2020.

She also contributes to open source projects such as GPy.

Contact Us

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

To contact the RSE team about seminars, training or JADE:

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