The Turing Lectures A series of inspiring talks by leading figures in data science and AI The Turing Lectures
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The Turing Podcast The Institute's podcast for discussions on all things data science, AI and machine learning The Turing Podcast
Equality, diversity and inclusion To make great leaps in research, we need to better reflect the diverse nature of the world Equality, diversity and inclusion
Research projects Simulating energy efficiency opportunities for households Developing synthetic housing microsimulation tools for local authorities to explore inequalities in energy efficiency and target homes in need of retrofit and fuel poverty support Simulating energy efficiency opportunities for households
Publication Trustworthy Assurance of Digital Mental Healthcare There is a culture of distrust surrounding the development and use of digital mental... Trustworthy Assurance of Digital Mental Healthcare
Research spotlight Premdeep Gill Enrichment student Premdeep Gill is studying Antarctic seals and their sea ice habitats through satellite data, to better understand how they are coping with climate change Premdeep Gill
Research spotlight Erin Young As co-lead of the Turing’s Women in Data Science and AI project, Research Fellow Erin Young’s vital research maps the gendered career trajectories in data science and AI Erin Young
Event Turing TIN Data Study Group – February 2023 Monday 13 Feb 2023 - Friday 03 Mar 2023 Time: 09:00 - 17:00 Turing TIN Data Study Group – February 2023
Data Study Groups Events bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges Data Study Groups
Partnering with the Turing We work with a wide range of partners to help deliver our mission of changing the world using data science and artificial intelligence Partnering with the Turing
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A common interface for discrete choice Assessing the viability of translating the ALOGIT software to Python and benchmarking it against other discrete choice modelling software
Adaptive multilevel MCMC sampling Developing an MCMC algorithm for efficient Bayesian inference in multilevel models
Analysing humanities books and newspapers data Text analysis using Cray's supercomputing analytics platform Urika-GX
Analysing social and geographic datasets Mapping the available tools and techniques for qualitatively understanding human behaviour, in the context of social dynamics
App-based information governance for trustworthy research environments Delivering an open source 'information governance system in a box' to support data protection in trustworthy research environments
Artificial intelligence for data analytics (AIDA) Drawing on new advances in AI and machine learning to address data wrangling issues, and help to automate the data analytics process
Automating data visualisation Researching algorithms for visualising data in digital twins, including automating the layout of large scale data and visualising the uncertainty of data values
Automating translation by determining text difficulty Building a model to determine the features of text which make it more difficult for machine translation
Chronotopic cartographies for literature Mapping fictional worlds from literary texts to advance understanding and interpretation of literature in entirely new ways
Data safe havens in the cloud Developing a policy and process framework for secure environments for productive data science research projects at scale
Data science toolkit for explorable data visualisations Helping scientists understand data analyses by connecting parts of visualisations to the data they depend on
Data science tools for high-performance computing Enabling the provision of popular data science packages within a managed, multi-user, academic high performance computing (HPC) environment
Decision-making under uncertainty in air traffic control Investigating machine learning methods to support air traffic controllers
Detecting and understanding harmful content online Developing benchmarks and datasets for online harms researchers, and guidance for practitioners using tools to detect online harms
Enabling meta-learning in Shogun.ML Allowing data scientists to exchange and analyse their workflows more easily
Environmental monitoring: blending satellite and surface data Intelligent fusion of data from satellite and in-situ surface sensors to help understand our changing planet
Evaluating homomorphic encryption Exploring different ways of encrypting sensitive data that can allow for secure, outsourced computation in the cloud
Global urban analytics for resilient defence Understanding the mechanics that cause conflict and identifying multi-scale population areas that are at risk of conflict
Improving Android game recommendations Creating a deep learning based tool to improve game recommendations on Samsung Galaxy devices
Integrating information visualisation with machine learning Integrating interactive data and information visualisation with machine learning technologies for learning for large datasets
Investigating industrial CT scanner damage Gathering community-sourced data on damage to x‑ray detectors in industrial CT scanners, to inform cost-effective maintenance
Language models for quantitative science studies Developing models to represent the use of language in research and improve performance of specific tasks, including the retrieval and summarisation of literature
Living with Machines A five-year research project that will take a fresh look at the well-known history of the Industrial Revolution using data-driven approaches
London air quality Developing machine learning algorithms and data science platforms to understand and improve air quality over London
Machine learning in Julia Developing a machine learning toolbox for the Julia programming language, emphasising ease of use, reproducibility, high performance, rapid development and advanced interoperability.
Managing uncertainty in government modelling Developing practical methods and tools for managing uncertainty in government modelling
Network modelling of the UK's urban skill base Modelling networks of locally embedded knowledge and skills to investigate the future diversification potential of individual UK cities
Nocell: Probabilistic programming for spreadsheet experts Developing a programming language for probabilistic model-building, for organisations that produce spreadsheets as output
Optimising analysis of network graphs Investigating how to optimise software that allows for the analysis of complex data networks on state-of-the-art processors
Optimising flow within mobility systems with AI Using interactive data visualisation, mathematical and computer modelling, and machine learning to transform the way cities are planned and urban traffic is managed
Project Bluebird: An AI system for air traffic control Advancing probabilistic machine learning to deliver safer, more efficient, and predictable air traffic control
QUIPP – Quantifying utility and preserving privacy in synthetic data sets Understanding the balance between utility, privacy and the uncertainty associated with synthetic data sets
Raphtory: A practical system for the analysis of dynamic graphs Developing an open source system for dynamic graph analysis of datasets
Safety of offshore floating facilities Predicting the hazardous conditions faced by offshore oil and gas facilities, to inform and improve operational decision-making
Scalable regression: Tools and techniques Developing techniques for regression models to scale at large data volumes, incorporating regression model power into big data analytics engines
Scalable topological data analysis Developing software that enables meaningful conclusions to be drawn from the shape of massive, noisy, and potentially incomplete datasets
Security in the cloud Investigating and prototyping the secure software components needed to enable data sharing without compromising data privacy.
Simplifying the setup of simulations Developing an intuitive framework to allow researchers to setup, configure and run simulation jobs, using different simulation packages and computing resources
sktime: A toolbox for data science with time series A unified toolbox for time series in the Python programming language
The (mis)informed citizen Using computational approaches to evaluate the quality of online news and studying its impacts
The Gamma: democratising data science Democratising data science by building tools that encourage everyone to understand data better
The Turing Way An open source and community-led handbook for reproducible, ethical and collaborative data science
Turing benchmarking framework Developing a cross-architecture benchmarking framework for data science algorithms
UK Biobank activity recognition Using deep learning to find new connections between patterns of physical activity and health outcomes
Uncertainty quantification of multi-scale and multi-physics computer models Developing new tools to investigate and quantify uncertainties in computer models, with applications to climate, earthquake and tsunami models
Visual diagnostics for Markov Chain Monte Carlo (MCMC) Designing visual diagnostics that articulate the concepts underlying robust MCMC computational algorithms
Visualising data profiles and analysis pipelines Investigating and developing visualisation techniques for profiling data and designing data processing pipelines
WAYS: What aren’t you seeing? Enhancing everyday visualisation practice through generative and evaluative design tools for data scientists
Web domain discovery Developing a scalable way to discover previously unknown government services on the web