Prediction algorithms with a causal interpretation
Monday 10 Feb 2020 - Wednesday 19 Feb 2020
Time: 09:00 - 17:00
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Modelling (Statistical methods & theory)
Projects
Pilot with authority for the financial markets
Developing an agent-based market simulator that can be used to test policy hypotheses
Economics nowcasting
Building methods to allow rapid assimilation of disparate data in national statistical estimates
Economic networks and transaction data
Developing a UK firm-to-firm payments/monetary flows dataset based on payments systems data to improve quality of economic analysis on key topics for UK policy makers
Input-output analytics for urban systems
Investigating inter-city trade flows in contemporary and historical contexts
Quantitative Urban ANalyTics (QUANT)
A land use transportation model simulating the location of employment, population and transport interactions
Disease trajectories following a heart attack
Investigating the use of process mining techniques to understand disease pathways amongst 145 million hospitalisation records
Personalising treatment in type 2 diabetes
Developing and testing a decision support tool for primary care to optimise the selection of glucose-lowering therapy for people with type 2 diabetes
Programmes
Data science for science and humanities
Ensuring that research across science and the humanities can make effective use of state of the art methods in artificial intelligence and data science
Publications and software
Bayesian statistics and modelling
Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available...
van de Schoot, R., Depaoli, S., King, R. et al. Bayesian statistics and modelling. Nat Rev Methods Primers 1, 1 (2021). https://doi.org/10.1038/s43586-020-00001-2
Predicting Infectiousness for Proactive Contact Tracing
The COVID-19 pandemic has spread rapidly worldwide, overwhelming manual contact tracing in many countries...
Bengio, Yoshua, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller et al. "Predicting Infectiousness for Proactive Contact Tracing." ICLR 2020.
Project Odysseus
Won CIUK Student Poster Competition 2020
Patrick O'Hara, James Walsh, Chance Haycock, Edward Thorpe-Woords, Oluwafunmilola Kesa, Andrew Wang, Mihai Ilas, James Brandreth, Oscar Giles, Neil Dhir, Theodoros Damoulas, Computing Insight UK 2020.
Explicit Regularisation in Gaussian Noise Injections
We study the regularisation induced in neural networks by Gaussian noise injections (GNIs). Though...
Camuto, A., Willetts, M., Şimşekli, U., Roberts, S., & Holmes, C. (2020). Explicit Regularisation in Gaussian Noise Injections. NeurIPS
A characterisation of the reconstructed birth–death process through time rescaling
The dynamics of a population exhibiting exponential growth can be modelled as a birth–death...
Theoretical Population Biology (2020) 134: 61-76
Data Study Group Final Report: Roche
Personalised lung cancer treatment modelling using electronic health records and genomics
Data Study Group team. (2020, June 4). Data Study Group Final Report: Roche. Zenodo. http://doi.org/10.5281/zenodo.3876989
Data Study Group Network Final Report: Rothamsted Research
Tackling hidden hunger through soils
Data Study Group team. (2020, April 29). Data Study Group Network Final Report: Rothamsted Research. Zenodo. http://doi.org/10.5281/zenodo.3775489
Data Study Group Final Report: eGym
Improved strength training using smart gym equipment data
Data Study Group team. (2020, April 17). Data Study Group Final Report: eGym. Zenodo. http://doi.org/10.5281/zenodo.3755606
Data Study Group Final Report: Great Ormond Street Hospital
Augmenting clinical decision-making in intensive care
Data Study Group team. (2020, February 17). Data Study Group Final Report: Great Ormond Street Hospital. Zenodo. http://doi.org/10.5281/zenodo.3670726
Articles
Digital twin technology a ‘powerful tool’ but requires significant investment, say experts
Digital twins at scale require a drastic reduction in barriers to adoption.
Monday 24 May 2021
New Nature research highlights the epidemiological impact of the NHS COVID-19 app
Evidence supporting continued development and deployment of contact tracing apps.
Wednesday 12 May 2021
Demonstrating the impact of the NHS COVID-19 app
Statistical analysis from researchers supporting the development of the NHS COVID-19 app
Tuesday 09 Feb 2021
Updates to the algorithm underlying the NHS COVID-19 app
Using Bayesian statistics to further improve the NHS contact tracing app’s performance
Thursday 29 Oct 2020
A technical roadmap for the UK’s contact tracing app functionality
A successful app is able to appropriately assess risk
Thursday 13 Aug 2020
Events
The Turing Lectures: What are YOUR chances?
Thursday 30 Sep 2021
Time: 16:30 - 18:00
On the dangers of stochastic parrots
Thursday 08 Jul 2021
Time: 16:00 - 17:15
Methodological challenges in the translation of data and evidence into policy during COVID-19
Friday 21 May 2021
Time: 16:00 - 17:00
TMCF workshop series: Prediction algorithms with a causal interpretation (online event)
Wednesday 06 May 2020
Time: 11:00 - 16:30
Network Science in Financial Services
Friday 06 Dec 2019
Time: 09:30 - 14:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Effective and efficient gaussian processes
Wednesday 07 Aug 2019
Time: 10:00 - 18:00
Skills-based modelling of economic development paths
Thursday 06 Jun 2019
Time: 13:30 - 17:30
Statistical trends in personalised healthcare
Monday 29 Apr 2019
Time: 10:15 - 18:00
Impact stories
Improving lives in Bradford
A collaboration between the Turing and Leeds Institute for Data Analytics is using data science to generate targeted policies for Bradford’s most deprived areas
Interest groups
Biodiversity monitoring and forecasting
How can we best catalyse and champion the development of new AI and data-driven methods for monitoring and forecasting biodiversity change?
Health equity
How can we ensure that developments and applications of data science and AI improve everyone’s health?
Bridging machine learning and behaviour models
How can we bridge data-driven and theory-driven behavioural models?
Learning the organisational principles of living systems
Can machine learning and AI help us to discover organisational principles of living systems?
Machine learning for radio frequency applications
How do we generate robust, real-time machine learning algorithms with integrated hardware and software for radio frequency applications?
Omics data generation and analysis group
Developing rigorous and robust data science methods for curation, collection and computation of omic data sets
People
Dr Sharana Shivanand
Research Associate
Dr Eleni-Rosalina Andrinopoulou
Assistant Professor at the Department of Biostatistics, Erasmus MC Rotterdam
Sonal Srivastava
Enrichment Student
Amber Emmett
Enrichment Student
Xue Gong
Enrichment Student
Pierre-Aurelien Gilliot
Enrichment Student
Elisa Rauseo
Enrichment Student
Vivienne Leech
Enrichment Student