Current members of the Research Software Engineering team are listed below. Previous members of the team can be found on our Alumni page.
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 is a Research Software Engineer who is currently:
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 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:
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 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 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 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.
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 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:
Open source research technologies and culture enabling next generation open science.
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] (http://www.flamegpu.com/) and advocating the use of GPU computing to support research. He is currently improving the performance of a model of tuberculosis spread.
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:
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.
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 (http://gpss.cc/) and the Women in Machine Learning (WiML https://wimlworkshop.org/), where she was the senior programme chair at the affinity workshop for ICML 2020.
She also contributes to open source projects such as GPy.
For queries relating to collaborating with the RSE team on projects: firstname.lastname@example.org
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