Current members of the Research Software Engineering team are listed below. Previous members of the team can be found on our Alumni page.
Romain joined the RSE Team as Head in August 2023. Prior to coming to the University of Sheffield he was a staff Astronomer at the European Southern Observatory (Chile) where he led the development of the SCUBA software framework, a tool dedicated to control the quality of more than 15 Very Large Telescope (VLT) instruments.
Romain holds a PhD in Astrophysics and Cosmology carried out at the Laboratoire D’Astrophysique de Marseille, France. He then went for a postdoc at the Universidad de Valparaiso, Chile and became a fellow at the European Southern Observatory a couple of years later. During his research time, Romain focused on the study of high redshift galaxies using large galaxy survey conducted mainly at the VLT. Romain has published various modules/software related to his work in astronomy (SPARTAN,dfitspy, SEDOBS, Photon).
Edwin joined the RSE team in October 2022. He comes from a background in geophysics following a BSc and MSc in Geophysical Sciences at the University of Leeds. After university, he worked in the private sector, developing machine learning (ML) workflows to solve geophysical imaging and inversion problems.
Edwin spends 50% of his time working in the Sheffield RSE team and the rest working in the Research Engineering Group (REG) at the Alan Turing Institute. Edwin has been working on a series of projects with the Sheffield Solar group in the School of Mathematical and Physical Sciences on the topic of modelling electricity demand in collaboration with various industry partners.
Edwin has practical experience in the designing, training and evaluation of ML models. He is experienced in Python having worked with data science libraries such as Pytorch, Tensorflow, tranformers and XGBoost. He has a growing interest in MLOps (Machine Learning Operations) and the practical challenges of scaling up ML practices.
Twin is a Senior 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.
Daniele joined the RSE team in 2020. He mainly supports:
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:
Contacts:
Dan joined the RSE team in December 2022. His background is in Cognitive Neuroscience, completing his PhD at Goldsmiths in 2016. Since then he has worked as a Research Fellow at Birkbeck and the University of Surrey and as Research Technician at the University of Reading. He has experience of writing research software and analysis pipelines using R, Python and Julia. He is also a keen advocate of open and reproducible research practices.
Robert is a Research Software Engineer that previously completed his PhD at the University of Sheffield. He specialises in performance optimisation and GPU parallelisation, following his PhD’s focus on improving the performance of spatial communication in GPU accelerated algorithms.
As a developer of the FLAMEGPU software framework, which facilitates wider access to complex systems modelling on GPUs, he has supported projects ranging from EU funded biological modelling to industrially funded transport modelling.
Since the 2022/2023 academic year he has been the module leader for COM4521/COM6521 that covers parallel programming with OpenMP and CUDA. He also reguarly supervises a small number of undergraduate projects within the school of computer science.
He is also a strong advocate for making software performance best practices accessible to programmers at all skill-levels. First he developed the Profling & Optimisation for Python short-course which is reguarly delivered to researchers at Sheffield. More recently he founded the “Reasonable Performance Computing” Special Interest Group, with support from the Society of Research Software Engineering, to more broadly gather and disseminate performance best practices at a national level. In 2025 he recieved an Software Sustainability Institute fellowship to support this work.
Shaun joined the RSE team in December 2024. He completed his PhD in Computational Chemistry at Aberystwyth University as part of the Solar Research Group in collaboration with the ExoMol Group at University College London. During his PhD, he developed two data sets, known as linelists, predicting the emission spectra of the diatomic molecules Strontium Hydride (SrH) and Barium Hydride (BaH). These linelists were generated using computational methods based on first principles and further refined with experimental spectroscopic data. During this time he developed experience in electronic structure theory and computational chemistry methods (MCSCF and MRCI).
In July 2023, he joined the Hill Research Group at the University of Sheffield, where he contributed to the development of the BasisOpt package for basis set optimisation and developed a machine learning model for predicting molecule-specific basis sets.
Martin joined the RSE team in 2024, and is based in the School of Mathematical and Physical Sciences. He completed his PhD in astronomy at the University of Sheffield in 2020, after which he continued working as a postdoc in the astronomy group before transitioning to a role as a research software engineer.
Martin’s primary focus is the Gravitional-wave Optical Transient Observer (GOTO) project, an international network of robotic survey telescopes which monitor the night sky for transient sources. During his PhD Martin developed the control and scheduling system for the GOTO telescopes, which are located on La Palma in the Canary Islands and in New South Wales, Australia. He is also a member of the ULTRACAM/HiPERCAM collaboration, which operates several high-speed astronomical cameras located at some of the world’s premier observatories.
Michael joined the RSE team in October 2024. He comes from a background in Computer Science, following an integrated masters degree and PhD in software testing at the University of Sheffield. After that, he was a research associate on the CITCoM project in the software testing group, also at the University of Sheffield. During this time, he has been an active member of the software engineering research community and an advocate for good research software practice, having served as a dedicated software reviewer for several software engineering conferences.
Michael’s main expertise is in black-box testing of traditionally “hard to test” software through the analysis of software logs and time series data. He is experienced in Python, and has worked with data science libraries such as Numpy, Pandas, and Statsmodels. He also has experience in functional programming, formal methods, code optimisation, and parallelisation.
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.
Tamora joined the RSE team in November 2023. She began her career in web and software development, working for over a decade in a variety of roles, before returning to academia to complete an MRes in population ecology and a PhD in conservation demography at the University of Sheffield. While studying for her PhD she became interested in how she could use her background in software development to help other researchers to improve their research software outputs by teaching them about commonly used tools and practices such as version control.
After completing her PhD in 2020, she joined the Centre for Environmental Modelling and Computation (CEMAC) at the University of Leeds as a Software Development Scientist, initially supporting the Global Challenges Research Fund African Science for Weather Information and Forecasting Techniques (GCRF African SWIFT) project. While at Leeds she worked on a range of projects including automated synoptic plotting for operational forecasting in Africa, visualisation of climate co-benefits, detection of biometeors using radar data, and the FASTA mobile app for near-real time weather forecasting (nowcasting) in Africa.
She has experience in writing research software using R and Python, and she has developed and led training in version control and reproducible research practices since 2016. She has been a co-organiser of Sheffield R Users Group since 2017.
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.
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 at University of Manchester, and University of Western Australia before returning to University of Sheffield learning UNIX system administration and literate programming along the way. 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 achieving 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 driver behaviour. Here he developed an understanding of working with geo-spatial data and learnt Python along with various aspects of good software development practices including working collaboratively using Git for version control.
Current projects:
Interests include:
Contact:
For queries relating to collaborating with the RSE team on projects: rse@sheffield.ac.uk
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