The Turing Lectures: What are YOUR chances?
Thursday 30 Sep 2021
Time: 16:30 - 18:00
Search
Neural networks
Webinar: Edge computing for Earth observation
Tuesday 17 Mar 2020
Time: 10:00 - 18:00
Machine learning interpretability, explainability and trustability
Wednesday 11 Mar 2020
Time: 18:00 - 20:30
Creativity and design in AI
Monday 18 Nov 2019
Time: 15:00 - 17:30
AI to advance wellbeing and society
Tuesday 06 Aug 2019
Time: 14:30 - 16:30
Towards Autonomous Robotic Systems Conference (TAROS)
Wednesday 03 Jul 2019 - Friday 05 Jul 2019
Time: 09:00 - 18:00
Deep Learning: working with convolutional neural networks – a hands on workshop
Tuesday 17 Jul 2018
Time: 14:00 - 17:00
Safety Verification of Deep Neural Networks
Friday 16 Jun 2017
Time: 18:37
Turing Lecture: Mathematics
Wednesday 02 Mar 2016
Time: 13:30 - 17:00
Projects
Neural-Symbolic AI for Digital Twins
Integrating symbolic reasoning with cutting-edge deep learning for trustworthy, interpretable, and explainable next-generation digital twin models.
Demoland
Spatial modelling for (urban) land management predicting the impact of large-scale planning and land use changes.
AMBER (AI-assisted Monitoring of Biodiversity using Edge-processing and Remote sensors)
Automated biodiversity monitoring of insects, bats and birds
AMBER (AI-assisted Monitoring of Biodiversity using Edge-processing and Remote sensors)
Automated biodiversity monitoring of insects, bats and birds
Machines reading maps
Creating a generalisable machine learning pipeline to process text on maps and catalysing humanities, scientific, and cultural heritage communities to use map text as data
Interpretable disease prediction models using supervised learning
Evaluating supervised machine learning models for creating interpretable disease risk prediction models using electronic health records
Risk prediction in adult cardiac surgery
Using machine learning to identify patients who are likely to not survive open heart surgery in the UK
Programmes
Publications and software
Polygonal Unadjusted Langevin Algorithms
Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. Lim, D-Y. & Sabanis, S. 2021. arXiv:2105.13937 [cs.LG]
tBERT – Topic Models and BERT Joining Forces for Semantic Similarity Detection
Semantic similarity detection is a fundamental task in natural language understanding. Adding topic information...
Nicole Peinelt, Dong Nguyen, Maria Liakata (2020): tBERT - Topic Models and BERT Joining Forces for Semantic Similarity Detection. Proceedings of the 58th Conference of the Association for Computational Linguistics (ACL 2020), pages 7047-7055.
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.
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
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
Deriving Equations from Sensor Data Using Dimensional Function Synthesis
We present a new method for deriving functions that model the relationship between multiple...
Youchao Wang, Sam Willis, Vasileios Tsoutsouras, and Phillip Stanley-Marbell. 2019. Deriving Equations from Sensor Data Using Dimensional Function Synthesis. ACM Trans. Embed. Comput. Syst. 18, 5s, Article 84 (October 2019), 22 pages. DOI:https://doi.org/10.1145/3358218
Taming neural networks with TUSLA: Non-convex learning via adaptive stochastic gradient Langevin algorithms
Artificial neural networks (ANNs) are typically highly nonlinear systems which are finely tuned via...
Taming neural networks with TUSLA : Non-convex learning via adaptive stochastic gradient Langevin algorithms. Lovas, Attila; Lytras, Iosif ; Rásonyi, Miklós ; Sabanis, Sotirios. arXiv:2006.14514 [cs.LG]
Data Study Group Final Report: WWF
Smart monitoring for conservation areas
Data Study Group team. (2020, June 5). Data Study Group Final Report: WWF. Zenodo. http://doi.org/10.5281/zenodo.3878457
Articles
Where do we draw the line?
Using data science to explore diversity of handwriting styles
Thursday 17 Dec 2020
Events
The Turing Lectures: What are YOUR chances?
Thursday 30 Sep 2021
Time: 16:30 - 18:00
Webinar: Edge computing for Earth observation
Tuesday 17 Mar 2020
Time: 10:00 - 18:00
Machine learning interpretability, explainability and trustability
Wednesday 11 Mar 2020
Time: 18:00 - 20:30
Creativity and design in AI
Monday 18 Nov 2019
Time: 15:00 - 17:30
AI to advance wellbeing and society
Tuesday 06 Aug 2019
Time: 14:30 - 16:30
Towards Autonomous Robotic Systems Conference (TAROS)
Wednesday 03 Jul 2019 - Friday 05 Jul 2019
Time: 09:00 - 18:00
Deep Learning: working with convolutional neural networks – a hands on workshop
Tuesday 17 Jul 2018
Time: 14:00 - 17:00
Safety Verification of Deep Neural Networks
Friday 16 Jun 2017
Time: 18:37
Magic Pony Technology: Artificial Intelligence, Neural Networks and Image Processing
Tuesday 07 Mar 2017
Time: 17:37
Impact stories
Mapping habitats in the Peak District National Park
An AI-powered tool is guiding wildlife monitoring and landscape restoration
Interest groups
Novel data linkages for health and wellbeing
How can we use novel digital footprint data for research to benefit health and wellbeing?
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?
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 Natalia Efremova
Senior Research Fellow, Environment and Sustainability
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
Dr Edmund Dable-Heath
Data Scientist