Quantitative Urban ANalyTics (QUANT) A land use transportation model simulating the location of employment, population and transport interactions
Ground truth for mental health data science Linking digital footprint data in the UK birth cohorts to guide the next generation of algorithms for mental health and wellbeing research
Project Odysseus – Understanding London ‘busyness’ and exiting lockdown Capturing activity over London to better understand 'busyness' and aid effective policy-making strategies for exiting the pandemic lockdown
Digital twins for multiphase flow systems Integrating data, physics and machine learning to develop rapid predictive models for engineered multiphase flow systems
AI for control problems Using a competition platform to accelerate progress in data-driven control problems
Synthetic population estimation and scenario projection Producing high resolution population projections and a framework for exploring future scenarios
Turing GeoVisualization Engine Developing a web-based visual analytics tool for geo-spatial data science
Digital twins for infrastructure and construction Developing the mathematical and statistical underpinnings of digital twins of assets such as bridges
An analytics dashboard for A&E Developing a digital tool that uses advanced analytics to assist A&E nurses in safely triaging the most critical patients
Research Engineering Connecting research to applications, helping create usable and sustainable tools, practices and systems.
Why practical data analytics is still so painful... and how we can help Datadiff Often an analyst is given a number of datasets from successive time periods... Wednesday 06 May 2020
In praise of research engineering A personal story from a departing Senior Research Data Scientist Wednesday 26 Jun 2019
Reliability and reproducibility in computational science Friday 24 Jan 2020 Time: 09:30 - 17:00 Peter V. Coveney Dan Crommelin Onnie Luk Nick Malleson Anna Nikishova
Software Citation Monday 13 May 2019 - Tuesday 14 May 2019 Time: 13:00 - 16:30 Kirstie Whitaker James Hetherington
Helping London to navigate lockdown safely Project Odysseus monitors activity on the streets of London, allowing authorities to make interventions to keep people socially distanced
A machine learning revolution in disaster response Turing researchers have combined crowd-sourcing, machine learning and neural networks to rapidly reveal the many dimensions of natural disasters, deploying the technology in the aftermath of Hurricane Dorian
Understanding urban air quality Turing researchers are working with the Greater London Authority to use machine learning and statistical methodology to better analyse air pollution sensor data, design better policy interventions, and improve urban quality of life
Making simulations simpler Software engineers at the Turing, in collaboration with partners at Imperial College and UCL, have developed a user interface which aims to make running simulations more user-friendly, for both academic and industrial communities
Data science for engineering structural integrity How can data science be used to improve the assessment of structural integrity across engineering sectors?
Game AI How can we advance the state of the art in game AI and apply it to ever more interesting and important problems, in games and beyond?