Previous members of the RSE Sheffield team:

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.

  • Twitter: @annakrystalli

Becky Arnold

Becky is a Research Software Engineer who worked with the University of Sheffield RSE group and the Alan Turing institute developing open-source guidance on best practice for reproducible data science. She took a leave of absence from her astrophysics research (where she uses simulations to study the evolution of star clusters) to work on this project.

She is also a Software Sustainability Institute fellow and is using the fellowship finds to organise a series of talks and workshops on a diverse range of topics surrounding best practice.

  • Email:

David Jones

David was 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.

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.

John Charlton

John was a PhD student and Research Software Engineer. Previous work had involved simulating dense crowds of virtual pedestrians, using GPUs to model many tens of thousands of people in real time. His interests included 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.

Mike Croucher

Mike is now head of Research IT at the University of Leeds. He is also an EPSRC Research Software Engineering Fellow with 10+ years experience supporting scientific software, high performance computing and research software engineering at The University of Manchester and, more recently, the University of Sheffield. Mike specialises in high-level languages such as MATLAB, R, Python and Mathematica but also has significant experience with compiled languages such as C and Fortran and assists researchers in developing faster, more robust, more usable code. Mike writes about research software on his blog,, which receives over 500,000 visitors annually.

He is an accredited Software Carpentry and Data Carpentry instructor.

Mozhgan Kabiri Chimeh

Dr Mozhgan Kabiri Chimeh is a GPU developer advocate at NVIDIA helping to bring GPU and HPC to growing user community in Europe and around the world. She is a community builder with a passion for open source software and is actively involved in the HPC and RSE communities. As a Software Sustainability Institute fellow, and Research Software Engineer (RSE) advocate, she is actively promoting reproducible and sustainable software, use of HPC and particularly GPUs through training, seminars, research software consultancy and outreach.

Prior to joining Nvidia, Mozhgan was a Research Software Engineer in Massive Scale Complex Systems Simulation with Accelerated Computing at the University of Sheffield, UK. She worked in the area of complex system modelling using emerging high-performance parallel architectures.

Mozhgan served as the chair of the women in HPC series of workshops at the International Supercomputing Conference and was on the organizing and program committee of leading conferences in the HPC field. She holds a Ph.D. in computer science and a master’s degree in Information Technology from the University of Glasgow, UK.

Phil Tooley

Phil is a Research Software Engineer and former theoretical and computational physicist, with particular interest in mathematical modelling, code optimisation and parallelism. He is an experienced developer of “traditional” parallel HPC codes using MPI and OpenMP in C, C++ and Fortran, but also champions the use of the Numpy/Scipy stack for scientific computing with python. This includes the use of accelerator technologies including Numba and Cython to write custom python code which is speed competitive with traditional compiled languages, possible in conjunction with parallel frameworks such as Dask.

Tania Allard

Tania left RSE Sheffield for a Research Associate/Research Software Engineer position at the University of Leeds. She has a PhD in computational nanomechanics at the University of Manchester where she focused on the multi-scale modelling of biological and biocompatible materials. She is part of Open Dream Kit (a Horizon2020 project), which focuses on the set up of Virtual research environments. Her interests include data science/engineering, reproducible research and supporting research teams to develop and optimise complex data analysis workflows. Also, she is actively involved in community building, mentoring, and scientific outreach activities within and outside the University of Sheffield.

She is an accredited Software Carpentry and Data Carpentry instructor.

Will Furnass

Will was a Research Software Engineer who was previously:

  • 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.

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.