Uncertainty and risk
Wednesday 17 Mar 2021 - Friday 19 Mar 2021
Time: 14:00 - 17:00
Search
Time series
Network Science in Financial Services
Friday 06 Dec 2019
Time: 09:30 - 14:30
Data science for physics and astronomy scoping workshop
Monday 02 Dec 2019 - Tuesday 03 Dec 2019
Time: 10:30 - 16:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Projects
Trustworthy synthetic data in practice
Building a toolbox to generate and evaluate the trustworthiness, scalability, and usability of synthetic data, and co-ordinating synthetic data research
Pilot with authority for the financial markets
Developing an agent-based market simulator that can be used to test policy hypotheses
Novel methodologies for assessing and evaluating synthetic data
Aiming to quantitatively and robustly characterise the fidelity, diversity, and generalisation performance of synthetic data
Input-output analytics for urban systems
Investigating inter-city trade flows in contemporary and historical contexts
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
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
Impact of climate change on agriculture
Building next-generation models to support resilient agricultural policy
Programmes
Publications and software
Machines in the media: semantic change in the lexicon of mechanization in 19th-century British newspapers
The industrialisation process associated with the so-called Industrial Revolution in 19th - century Great...
Proceedings of the 2nd International Workshop on Natural Language Processing for Digital Humanities, pages 85–95, Taipei, Taiwan. Association for Computational Linguistics.
Diachronic word embeddings from 19th-century British newspapers
Diachronic word embeddings trained on a 4.2-billion-word corpus of 19th-century British newspapers, using Word2Vec...
Pedrazzini, Nilo & Barbara McGillivray. (2022). Diachronic word embeddings from 19th-century British newspapers [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7181682
Using wearable activity trackers to predict Type-2 Diabetes: A machine learning-based cross-sectional study of the UK Biobank accelerometer cohort
Background: Between 2013 and 2015, the UK Biobank (UKBB) collected accelerometer traces (AXT) using...
Lam B, Catt M, Cassidy S, Bacardit J, Darke P, Butterfield S, Alshabrawy O, Trenell M, Missier P
Data Study Group Final Report: Greenvest Solutions
Forecasting wind energy production using satellite data
Data Study Group team. (2021, February 11). Data Study Group Final Report: Greenvest Solutions. Zenodo. https://doi.org/10.5281/zenodo.4534349
Generalized Bayesian filtering via sequential Monte Carlo
We introduce a framework for inference in general state-space hidden Markov models (HMMs) under...
A. Boustati, Ö. D. Akylidìz, T. Damoulas, and A. M. Johansen (2020). Generalized Bayesian filtering via sequential Monte Carlo. In Advances in Neural Information Processing Systems 33 (NeurIPS). To appear.
Data Study Group Final Report: Telenor
Green Radio: Dynamic power saving configuration for mobile networks
Data Study Group team. (2020). Data Study Group Final Report: Telenor. http://doi.org/10.5281/zenodo.3786852
The future of sleep health: A data-driven revolution in sleep science and medicine
In recent years, there has been a significant expansion in the development and use...
Perez-Pozuelo, I., Zhai, B., Palotti, J. et al. The future of sleep health: a data-driven revolution in sleep science and medicine. npj Digit. Med. 3, 42 (2020). https://doi.org/10.1038/s41746-020-0244-4
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
Multi-Task Time Series Analysis applied to Drug Response Modelling
Time series models such as dynamical systems are frequently fitted to a cohort of...
Bird, A., Williams, C. K. I. and Hawthorne, C. (2019). Multi-Task Time Series Analysis applied to Drug Response Modelling. In The 22nd International Conference on Artificial Intelligence and Statistics (pp. 2174-2183).
Articles
Events
Uncertainty and risk
Wednesday 17 Mar 2021 - Friday 19 Mar 2021
Time: 14:00 - 17:00
Network Science in Financial Services
Friday 06 Dec 2019
Time: 09:30 - 14:30
Data science for physics and astronomy scoping workshop
Monday 02 Dec 2019 - Tuesday 03 Dec 2019
Time: 10:30 - 16:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Impact stories
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?
Meta-learning for multimodal data
How can we transfer knowledge across tasks and domains to improve machine learning on multimodal data?
Learning the organisational principles of living systems
Can machine learning and artificial intelligence help us to discover and understand biological principles?
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
Trustworthy Digital Identity Interest Group
How can we understand, evaluate and advance the trustworthiness of digital identity systems?
Machine learning and dynamical systems
How do we analyse dynamical systems on the basis of observed data, rather than attempt to study them analytically?
People
Dr Thijs van der Plas
Postdoctoral Research Associate
Dr Katie Awty-Carroll
Senior Data Scientist
Ye Wei
Enrichment Student
Victor Btesh
Enrichment Student
Skyler Xie
Enrichment Student
Munib Mesinovic
Enrichment Student
Lara Johnson
Enrichment Student
Jakob Wessel
Enrichment Student