Projects
AI for multiple long-term conditions: Research Support Facility
Developing data standards, best practice and community around AI for multiple long term conditions research
WAYS: What aren’t you seeing?
Enhancing everyday visualisation practice through generative and evaluative design tools for data scientists
Detecting and understanding harmful content online
Developing benchmarks and datasets for online harms researchers, and guidance for practitioners using tools to detect online harms
Optimising hypertension management strategies
Using smart algorithms to optimise treatment decisions in blood pressure management and reduce economic burden on healthcare providers
Programmes
Publications and software
Towards a quantitative research framework for historical disciplines
McGillivray, B., Wilson, J. and Blanke, T. (2019). Towards a quantitative research framework for historical disciplines. In Proceedings of the Workshop on Computational Methods in the Humanities 2018, Lausanne, Switzerland, June 4-5, 2018
Mining the UK Web Archive for Semantic Change Detection
Semantic change detection (i.e., identifying words whose meaning has changed over time) started emerging...
Tsakalidis, A., Bazzi, M., Cucuringu, M., Basile, P., & McGillivray, B. Mining the UK Web Archive for Semantic Change Detection. Proceedings of INTERNATIONAL CONFERENCE RECENT ADVANCES IN NATURAL LANGUAGE PROCESSING, https://doi.org/10.17863/CAM.43534
Towards a quantitative research framework for historical disciplines
The ever-expanding wealth of digital material that researchers have at their disposal today, coupled...
McGillivray, B., Wilson, J. and Blanke, T. (2019). Towards a quantitative research framework for historical disciplines. In Proceedings of the Workshop on Computational Methods in the Humanities 2018, Lausanne, Switzerland, June
Quantitative Historical Linguistics.
A Corpus Framework
Jenset, G. B. and McGillivray, B. (2017). Quantitative Historical Linguistics. A Corpus Framework, Oxford: Oxford University Press.
Events
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
Methodological challenges and approaches in COVID-19 epidemiology
Friday 23 Apr 2021
Time: 16:00 - 17:00
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Vocal interactivity in-and-between humans, animals and robots
Thursday 29 Aug 2019 - Friday 30 Aug 2019
Time: 09:00 - 17:00
Measuring information exposure in dynamic and dependent networks
Monday 22 Jul 2019
Time: 10:00 - 16:00
Urban analytics at the interface between environment, human health and behaviour
Tuesday 02 Jul 2019 - Thursday 04 Jul 2019
Time: 09:00 - 18:00
Real people behind artificial intelligence
Tuesday 22 Jan 2019
Time: 17:30 - 19:30
Automating the crowd
Tuesday 22 Jan 2019
Time: 10:00 - 17:00
Impact stories
Interest groups
Bridging machine learning and behaviour models
How can we bridge data-driven and theory-driven behavioural models?
Omics data generation and analysis group
Developing rigorous and robust data science methods for curation, collection and computation of omic data sets
Facilitating responsible participation in data science
What guidance do we need to have in place to ensure that stakeholder participation is meaningful, effective, and inclusive?
Economic data science
How can we use modern computational and statistical methods to analyse economic data?
People
Professor Jon Crowcroft
Researcher at Large
Emma Vestesson
Enrichment Student
Rafiah Patel
Enrichment Student
Ridda Ali
Enrichment Student
Luca Marinelli
Enrichment Student
William Finnegan
Enrichment Student
Hope Kent
Enrichment Student
Dr Joshua Rhodes
Research Associate