The Turing Lectures: Do you see what I see?
Tuesday 04 May 2021
Time: 16:00 - 17:30
Search
Unsupervised learning
Citizen participation and machine learning for a better democracy
Friday 07 Feb 2020
Time: 13:00 - 18:00
Statistics and computation
Monday 13 Jan 2020 - Tuesday 14 Jan 2020
Time: 10:00 - 17:00
Data science for physics and astronomy scoping workshop
Monday 02 Dec 2019 - Tuesday 03 Dec 2019
Time: 10:30 - 16:30
Creativity and design in AI
Monday 18 Nov 2019
Time: 15:00 - 17:30
Provenance, security & machine learning
Monday 11 Nov 2019
Time: 09:45 - 17:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Towards Autonomous Robotic Systems Conference (TAROS)
Wednesday 03 Jul 2019 - Friday 05 Jul 2019
Time: 09:00 - 18:00
Machine learning meets statistics
Monday 25 Mar 2019 - Tuesday 26 Mar 2019
Time: 09:30 - 16:15
Projects
The impact of emerging technologies on the financial services industry
Investigating the impact of developments in AI, Web3, and Quantum technologies on the financial services industry.
Pilot with authority for the financial markets
Developing an agent-based market simulator that can be used to test policy hypotheses
Network based recommender systems for public procurement
A novel methodology for community detection and link prediction with applications in public procurement
Interpretable disease prediction models using supervised learning
Evaluating supervised machine learning models for creating interpretable disease risk prediction models using electronic health records
The Turing AI scientist grand challenge
Developing AI systems capable of making Nobel quality scientific discoveries highly autonomously at a level comparable, and possibly superior, to the best human scientists by 2050
Synthetic data generation for finance and economics
Generating artificial business, finance, and economic data to enable data sharing, scenario simulation, and model validation
Publications and software
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: Dstl – Anthrax and nerve agent detector
Identification of hazardous chemical and biological contamination on surfaces using spectral signatures
Data Study Group team. (2021, February 11). Data Study Group Final Report: Dstl – Anthrax and nerve agent detector. Zenodo. https://doi.org/10.5281/zenodo.4534219
Learning Bijective Feature Maps for Linear ICA
Separating high-dimensional data like images into independent latent factors, i.e independent component analysis (ICA)...
Camuto, A., Willetts, M., Paige, B., Holmes, C., Roberts, S., (2020) Learning Bijective Feature Maps for Linear ICA
Improving VAEs’ Robustness to Adversarial Attack
Variational autoencoders (VAEs) have recently been shown to be vulnerable to adversarial attacks, wherein...
Willetts, M., Camuto, A., Rainforth, T., Roberts, S., Holmes, C., (2021) Improving VAEs’ Robustness to Adversarial Attack. International Conference of Learning Representations (ICLR)
Disentangling to Cluster
Gaussian Mixture Variational Ladder Autoencoders
Willetts, M., Roberts, S., Holmes, C. (2019) Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. NeurIPS Bayesian Deep Learning Workshop 2019
Development of a speech quality database under uncontrolled conditions
Objective audio quality assessment is preferred to avoid time-consuming and costly listening tests. The...
A. Ragano, E. Benetos, and A. Hines, "Development of a speech quality database under uncontrolled conditions", in Proc. 21st Annual Conference of the International Speech Communication Association (INTERSPEECH), Oct. 2020.
A baseline for unsupervised advanced persistent threat detection in system-level provenance
Advanced persistent threats (APTs) are stealthy, sophisticated, and unpredictable cyberattacks that can steal intellectual...
A baseline for unsupervised advanced persistent threat detection in system-level provenance, Ghita Berrada, Sidahmed Benabderrahmane, James Cheney, William Maxwell, Himan Mookherjee, Alec Theriault, and Ryan Wright, Future Generation Computing Systems Volume 108, July 2020, Pages 401-413.
Data Study Group Final Report: Spend Network
Automated matching of businesses to government contract opportunities
Data Study Group team. (2019, November 29). Data Study Group Final Report: Spend Network. Zenodo. http://doi.org/10.5281/zenodo.3558243
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
The interpretation of complex high-dimensional data typically requires the use of dimensionality reduction techniques...
Märtens, K., Campbell, K. R., Yau, C. (2019) Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4372-4381.
Articles
Where do we draw the line?
Using data science to explore diversity of handwriting styles
Thursday 17 Dec 2020
Events
The Turing Lectures: Do you see what I see?
Tuesday 04 May 2021
Time: 16:00 - 17:30
Citizen participation and machine learning for a better democracy
Friday 07 Feb 2020
Time: 13:00 - 18:00
Statistics and computation
Monday 13 Jan 2020 - Tuesday 14 Jan 2020
Time: 10:00 - 17:00
Data science for physics and astronomy scoping workshop
Monday 02 Dec 2019 - Tuesday 03 Dec 2019
Time: 10:30 - 16:30
Creativity and design in AI
Monday 18 Nov 2019
Time: 15:00 - 17:30
Provenance, security & machine learning
Monday 11 Nov 2019
Time: 09:45 - 17:30
Building a future for the urban analytics blueprint
Wednesday 16 Oct 2019 - Friday 18 Oct 2019
Time: 10:00 - 17:00
Towards Autonomous Robotic Systems Conference (TAROS)
Wednesday 03 Jul 2019 - Friday 05 Jul 2019
Time: 09:00 - 18:00
Machine learning meets statistics
Monday 25 Mar 2019 - Tuesday 26 Mar 2019
Time: 09:30 - 16:15
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?
Data-centric biological design and engineering
How can AI support the practical engineering of biology to tackle global challenges?
Meta-learning for multimodal data
How can we transfer knowledge across tasks and domains to improve machine learning on multimodal data?
Precision dementia medicine
How can we harness the power of data science and artificial intelligence to combat dementia and promote brain health?
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
People
Dr Alex Hickey
Research Engineering
Dr Noushin Eftekhari
Research Associate
Dr Thijs van der Plas
Postdoctoral Research Associate
Dr Katie Awty-Carroll
Senior Data Scientist
Boyko Vodenicharski
Data Scientist
Victor Btesh
Enrichment Student