Research IT Services


Research software development projects

Active projects

School of Laws, Arts & Humanities, and Social & Historical Sciences (SLASH)


Our work with the Open Richly Annotated Cuneiform project continues as part of project Nahrein ("two rivers" in Arabic), to help local middle eastern scholars have the tools to do their own digital humanities.

Oceanic Exchanges

We're working with the Oceanic Exchanges project to enable the analysis of large collections of newspaper articles, from multiple countries, on UCL's high performance computing platforms.

Bentham Transcription Desk migration

We're helping the Transcribe Bentham project to put their server technologies on a more stable footing.

  • PI: Prof. Philip Schofield
  • RSDG team: Tom Couch, Roma Kaplaukh
  • Duration: 2018
  • Languages and Technologies: Mediawiki, PHP

School of Education


School of the Built Environment, Engineering, and Mathematical and Physical Sciences (BEAMS)


We're contributing to the Zacros Project, a Kinetic Monte Carlo (KMC) software package written in Fortran, for simulating molecular phenomena on catalytic surfaces.


We're creating a web service for the BEM++ boundary element method code, to allow it to be combined with other tools into more complicated workflows and to create a web-based front end for commercial use. This follows on from previous work on parallelisation and refactoring for the simulation code itself.


We're contributing to this project to develop simulation pipelines for non-invasive surgery using High-Intensive Focus Ultrasound.

BICO: Big data compressive sensing

Collaborating with Dr Jason McEwen of the Mullard Space Science Laboratory, we are contributing to a reusable high performance framework for the application of compressive sensing to image cleanup, with application to the square kilometre array.


We're working with the Dirac STFC supercomputing project to benchmark physics and astronomy codes on different computing platforms and cloud providers.

School of Life and Medical Sciences (SLMS)

Big Data for Critical Care with the National Health Informatics Collaborative

We have an ongoing collaboration with the UCLH Critical Care team and colleagues at the Farr Institute in their work as part of the NHS Health Informatics Collaborative. Intensive Care provides rich, complicated, large, sensitive, high-speed data, with a great deal of data recorded about every patient every moment – as complete an example of the four V’s of big data (Volume, Variety, Velocity and Veracity) as you are likely to get. Together are building tools and systems to allow this data to be used for research, and ultimately, for real-time patient care.



The aim of this project is to improve the allocation and evaluation of critical care within UCLH. This will involve using existing electronic health records to monitor patients at risk of deterioration outside of intensive care units, enabling health care teams to make decisions on critical care admissions. Phase 1 will build a near-future forecasting system for ICU bed occupancy that takes into account the current workload and planned high-risk surgical admissions. Phase 2 will evaluate whether this decreases surgical cancellations, allows fairer allocation of beds and reduces harm by admitting the right patient at the right time. RSDG are working on extracting the data in various hospital systems and incorporating it into the modelling work.


This project with UCLH builds on our collaboration for the Health Informatics Collaborative to leverage the data pipeline built there for direct benefit within the hospital. It is an ambitious programme of work to define a research programming environment within the hospital's IT structures, and demonstrate value from this in various application areas. Initially, we will work to expand and improve the capture of historic and real time usable patient data. We will then be in a position to test and implement certain procedures which will improve patient outcomes within the Intensive Care Unit (prior to wider hospital dissemination), based on the new data systems and real-time monitoring.

Thanzi la Onse

This project's name means "Health of All' and is developing epidemiological models which we hope will ultimately inform decision-makers in Malawi on national health care budgets and in allocating resources. The team aims to explore ways to improve the health of the population in Malawi, as well as reducing health inequality in low and middle income countries. RSDG are providing the software framework for building and simulating the mathematical models involved.

HIV model conversion

This feasibility study will assess the effort required and potential benefits in converting a large HIV epidemiology model from SAS to Python. Should it look promising, funding will be sought to convert the entire model.

Delivering accurate structural bioinformatics to the yeast community with the HHprY data

Progress in cell biology is hampered by the relatively high proportion of proteins for which there is no known function at the molecular level. Such proteins have no domains annotated in the databases. Structural bioinformaticians have for many years been developing profile-profile search tools (such as the HHsearch tool developed by Soeding and colleagues) that are far more sensitive than the standard tools, but due to computational demand these tools have not been widely applied to create fully annotated complete genomes. We are working to deploy these tools on UCL supercomputing infrastructure, and we are developing an automated pipeline and web interface, to make available a fully augmented annotation of the entire yeast genome.

  • PI: Dr Tim Levine
  • Funding: BBSRC
  • RSDG team: Ilektra Christidi, Asif Tamuri, James Hetherington, Gary Macindoe
  • Languages and Technologies: Python, Flask
  • Links: HHYeast Server

FASt-Mal Laboratory Information Management System

Translating state-of-the-art robotics and machine-learning research into a benchtop prototype capable of Fast, Accurate and Scalable malaria diagnosis. The project aims to overcome diagnostic challenges by replacing human-expert optical-microscopy with a robotic automated computer-expert system that assesses similar digital-optical-microscopy representations of the disease. RSDG is developing the information management system for the project, storing acquired images with all metadata, allowing human experts to annotate images for training and test datasets, and interfacing with the machine learning software being developed by UCL Computer Science.

Modelling and Optimisation of Antibody Purification Processes

Multi-product biopharmaceutical facilities need flexible process configurations that can adapt to products with diverse characteristics and impurity loads so as to avoid bottlenecks and delays, whilst meeting final product specifications and cost targets. In this project we are working with the group to convert existing bioprocess models and optimisers from Excel and C# to Python. The emphasis is on making the model representations clear and easy for the researchers to modify, with robust testing to verify expected behaviour. We are also building web interfaces to these tools - Jupyter notebooks for use by researchers, and a Flask application for end users.

Mathematical Modelling Led Design of Tissue-Engineered Constructs

We will be creating a user-friendly interface to the mathematical models developed by the researchers on this project, which will help enable their update by tissue engineers and clinicians.

New tools in the fight against cystic fibrosis

Cystic fibrosis (CF) is the most common, lethal, genetic disorder amongst Europeans and is caused by loss-of-function mutations in a single gene. This project will develop new measurement tools for lung function, use these to assess cell cultures as models of what happens in CF, and hence accelerate drug discovery. RSDG will be involved developing software for the toolkit - open source interfaces to the hardware involved.

Reproducible model development with the Web Lab

Models are developed to answer specific scientific questions, and the process of model selection, parameterisation and evaluation is typically manual and laborious. There is no straightforward means to determine which (if any) model is the most appropriate to answer a new question, or be used as a component in a larger model. We aim to make the process of model development documented, automated and repeatable, so that models can easily be tested and updated to incorporate new data. In collaboration with modellers at Oxford, Nottingham and elsewhere, RSDG are building an online resource to run virtual experiments and automate the process of parameterisation of cardiac cell models from data by using state-of-the-art Bayesian inference methods.

Silver Lab: Neuroscience data analysis pipeline & OpenSourceBrain

The Silver Lab develops state-of-the-art acousto-optic lens (AOL) two-photon microscopes and uses these to gain understanding of neurophysiology. We are working to integrate and optimise various Matlab analysis scripts developed by lab members into a coherent analysis pipeline, with the data at each stage stored in the open NeurodataWithoutBorders format, based on HDF5. A second line of work is developing some new API libraries for NeuroML2 – a model description language for computational neuroscience.

UCL-wide Research


We're working with colleagues across ISD to develop an easy-to-use hybrid cloud facility for UCL researchers.

Completed projects

School of Laws, Arts & Humanities, and Social & Historical Sciences (SLASH)


The Open Richly Annotated Cuneiform Corpus (ORACC) supports editing of translations and transliterations of ancient Mesopotamian (Iraqi) texts. The principal aim of this project is to create a local GUI for ORACC.

DataSpring: Enabling complex analysis of large scale digital collections

Funded through the JISC "Research Data Spring" initiative, this project seeks to make it possible to efficiently query a corpus of 81000 out-of-copyright books using UCL's research computing infrastructure, and to thereby understand the issues that arise in using traditional HPC resources for humanities work

Times Digital Archive queries

Gaussian Process Emulator

Researchers in the Department of Geography have developed this code to monitor the historical and current state of terrestrial vegetation cover using satellite images. We are working to enable the most computationally intensive aspects of this code to run on GPUs in order to accelerate the analysis of these images.

School of the Built Environment, Engineering, and Mathematical and Physical Sciences (BEAMS)

Electrical Impedance Tomography

Prof. David Holder's group in the Department of Medical Physics and Biomedical Engineering have been pioneering the use of Electrical Impedance Tomography for imaging brain function. We are helping to identify areas of improvement in the software used to produce 4D EIT visualisations and mentoring the EIT team on how to adopt good software development practices.


We worked with Dr Nicolae Panoiu on the OPTIMET-3D code, a fast and massively distributed electromagnetic solver for advanced HPC studies of 3D photonic nanostructures. The objective is to further scale the code from running efficiently on Legion to running efficiently on ARCHER.

  • PI: Dr Nicolae Panoiu
  • Funding: Archer eCSE call
  • RSDG team: Mayeul D'Avezac, Gary Macindoe
  • Duration: September 2015 - August 2016
  • Languages and technologies: MPI, C

Radiance Monte Carlo

The aim of this project is to strike a performance/accuracy balance between Radiance Monte Carlo algorithms that operate on a polyhedral mesh (slow but accurate) and a regular grid (fast but less accurate) by using an Octree.

  • PI: Dr Ben Cox, Medical Physics and Biomedical Engineering
  • Funding: UCL
  • RSDG team: Mayeul D'Avezac, Gary Macindoe
  • Duration: 2015
  • Languages and technologies: C++11, MATLAB, Boost, CMake, VTK

Bahler Lab

  • PI:
  • Funding: RSDG free call
  • RSDG team: Sinan Shi
  • Duration: 2015
  • Links: www.bahlerlab.info

CWA Downsampling

  • RSDG team: Raquel Alegre, Stuart Grieve
  • Duration: September 2017 - May 2018
  • Languages and Technologies: Python, SQLAlchemy, Postgres


After a successful first round of collaboration we are now working to make further improvements to this open-source computational suite for fluid dynamics simulations of blood flow. We have combined an elastic model of a red blood cell with the underlying Computational Fluid Dynamics simulation of blood flow. Case study

ShipViz: AIS Data Visualisation

This project is funded by the European Climate Foundation to substantiate shipping policy debates with high-quality infographics. They need the RSD team to create 4D visualisations of ship tracks, similar to previous work they've done to help researchers analysing the 1 billion records of shipping tracks data.


GloTraM is a global transport model that combines multi-disciplinary analysis and modelling techniques to estimate foreseeable futures of the shipping industry, forecasting the evolution of a fleet and its activity in response to external stimuli: changing fuel prices, transport demand, regulation, technology availability...  

We are working with Dr. Tristan Smith and Dr. Carlo Raucci at the UCL Energy Institute to improve the status and performance of this model written in MatLab, enabling other projects which will be based on this outcome.


We acted as consultants to advise the UCL Energy Institute and Baringa consulting partners on software architecture for complex multi-scale models of the future of the UK energy and housing infrastructure.

School of Life and Medical Sciences (SLMS)


We helped Professor David Balding of the UCL Genetics Institute to prepare his forensic DNA analysis package for submission to CRAN, the online repository for sharing R packages. Case study

  • PI: Professor David Balding - UCL Genetics Institute
  • Funding: Free call
  • RSDG team: Mayeul D'Avezac
  • Duration: Jan-May 2015
  • Languages and technologies: R


We worked with Dr Ben Cox of to build a parallel simulation code for propagation of high frequency ultrasound in anisotropic media.

  • PI: Dr Ben Cox - Dept of Med Phys & Biomedical Eng
  • Funding: Free call
  • RSDG team: Mayeul D'Avezac
  • Duration: October 2013-March 2014
  • Languages and technologies:  eigen, cmake


We worked with researchers at Great Ormond Street Hospital and the UCL Institute for Child Health to develop a web interface for a new non-invasive downs syndrome test.

  • PI: Dr Chris Boustred - GOSH
  • Funding: Free call
  • RSDG team: Gary Macindoe
  • Duration: April - Aug 2014
  • Languages and technologies: Django, Celery


Abysis is an antibody discovery system supporting the analysis of antibody sequence and structure. We refactored the existing codebase and added new features such as the ability to discover and annotate patterns in antibody protein sequences.


HJCFIT is a library for the maximum likelihood fitting of kinetic mechanisms to sequences of open and shut time intervals from single-channel experiments. It is a part of the DCProgs suite of tools. In this project, we have transformed HJCFIT from a single-process library running on desktop computers to a multi-precision library that can utilise a full Archer node and is thus 14 times faster than the original serial version. We have implemented multi-precision arithmetic, made the code easier to use on high-performance systems and made several other improvements to the overall codebase.

RFH-GFR Web Calculator

The Glomerular filtration rate calculator based on research produced at the Royal Free Hospital and UCL. The GFR calculator is a web app for educational purposes that can provide insight on doctors taking care of patients with cirrhosis.

UCL-wide Research

Research Software Dashboard

This is a UCL-wide integrated web-based environment for UCL researchers to manage, share and promote their software research outputs. The dashboard consists of an automated online list of all the software created and maintained by UCL researchers. It allows UCL to promote and measure the quantity and quality of UCL computational research, raising the institution’s profile in this space, and facilitating both obtaining and delivering research grants with a significant software component.


Global River Concavity (Cardiff University)

Project to develop an HPC topographic analysis workflow using LSDTopoTools and Legion to quantify structural variations in river channel morphology with climate data at a global scale.

  • PI: Dr. Michael Singer
  • Faculty: School of Earth and Ocean Sciences, Cardiff University
  • Funding: Cardiff departmental funding
  • RSDG team: Stuart Grieve
  • Duration: 3 months
  • Languages and Technologies: python, bash, C++, LSDTopoTools
  • Links: https://github.com/sgrieve/concavity