Interpretability, safety, and security in AI
Monday 13 Dec 2021 - Wednesday 15 Dec 2021
Time: 11:00 - 18:00
Search
Algorithms
The Turing Lectures: Policy fights back
Wednesday 14 Jul 2021
Time: 15:00 - 16:30
The Turing Lectures: What are YOUR chances?
Thursday 30 Sep 2021
Time: 16:30 - 18:00
Turing Lecture: Building dynamic robots
Tuesday 22 Sep 2020
Time: 15:00 - 16:30
Reliability and reproducibility in computational science
Friday 24 Jan 2020
Time: 09:30 - 17:00
Reinforcement and mean-field games in algorithmic trading
Wednesday 27 Mar 2019
Time: 14:00 - 16:00
Mathematics of data
Wednesday 29 May 2019 - Friday 31 May 2019
Time: 10:00 - 17:00
Turing Lecture: Be prepared to show your working!
Tuesday 11 Dec 2018
Time: 18:15 - 20:30
Computational Semantics Evaluation: The Origins of Senseval and Evolution of SemEval
Monday 16 Jul 2018
Time: 10:30 - 12:00
Projects
London Air Quality Impact
Maximising the impact of the London Air Quality project by demonstrating live pollution forecasting
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
Predictive graph analytics and propagation of information in networks
Leveraging graph optimisation tools to understand how news sentiment spreads in a financial network
Machine learning in Julia
Developing a machine learning toolbox for the Julia programming language, emphasising ease of use, reproducibility, high performance, rapid development and advanced interoperability.
Data science tools for high-performance computing
Enabling the provision of popular data science packages within a managed, multi-user, academic high performance computing (HPC) environment
Scalable regression: Tools and techniques
Developing techniques for regression models to scale at large data volumes, incorporating regression model power into big data analytics engines
Programmes
Publications and software
Identifying key players in dark web marketplaces
Dark web marketplaces have been a significant outlet for illicit trade, serving millions of...
dos Reis, E.F., Teytelboym, A., ElBahrawy, A. et al. Identifying key players in dark web marketplaces through Bitcoin transaction networks. Sci Rep 14, 2385 (2024). https://doi.org/10.1038/s41598-023-50409-5
Data Study Group Final Report: The National Archives, UK
Discovering topics and trends in the UK government web archive
Data Study Group team. (2021, June 18). Data Study Group Final Report: The National Archives, UK. Zenodo. https://doi.org/10.5281/zenodo.4981184
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
Multispectral snapshot demosaicing via non-convex matrix completion
Snapshot mosaic multispectral imagery acquires an undersampled data cube by acquiring a single spectral...
Giancarlo A. Antonucci, Simon Vary, David Humphreys, Robert A. Lamb, Jonathan Piper, Jared Tanner, "Multispectral snapshot demosaicing via non-convex matrix completion", IEEE Data Science Workshop, Univ. of Minnesota, June 2019
On the construction of sparse matrices from expander graphs
We revisit the asymptotic analysis of probabilistic construction of adjacency matrices of expander graphs...
Bubacarr Bah, and Jared Tanner, “On the construction of sparse matrices from expander graphs”, Frontiers in Applied Mathematics and Statistics (2018)
Matrix rigidity and the ill-posedness of Robust PCA and matrix completion
Robust Principal Component Analysis (PCA) (Candes et al., 2011) and low-rank matrix completion (Recht...
Jared Tanner, Andrew Thompson, Simon Vary, “Matrix rigidity and the ill-posedness of Robust PCA and matrix completion”, SIAM Mathematics of Data Science, accepted
Sparse Inverse Problems Over Measures: Equivalence of the Conditional Gradient and Exchange Methods
We study an optimization program over nonnegative Borel measures that encourages sparsity in its...
Eftekhari, Armin, and Andrew Thompson. "Sparse Inverse Problems over Measures: Equivalence of the Conditional Gradient and Exchange Methods." SIAM Journal on Optimization 29.2 (2019): 1329-1349.
Data Study Group Final Report: PlayerLens
Player pathways: Understanding career paths that deliver success for professional football players and clubs
Data Study Group team. (2019, November 29). Data Study Group Final Report: PlayerLens. Zenodo. http://doi.org/10.5281/zenodo.3558253
Articles
Turing researchers call for changes to data protection law to protect consumer and individual privacy
Data protection law (meant to protect people’s privacy, identity, reputation and autonomy) is currently...
Friday 14 Sep 2018
Turing responds to Science and Technology Committee report on algorithms in decision-making
We welcome the new report, Algorithms in decision-making, from the House of Commons Science...
Wednesday 23 May 2018
Events
Interpretability, safety, and security in AI
Monday 13 Dec 2021 - Wednesday 15 Dec 2021
Time: 11:00 - 18:00
The Turing Lectures: What are YOUR chances?
Thursday 30 Sep 2021
Time: 16:30 - 18:00
The Turing Lectures: Policy fights back
Wednesday 14 Jul 2021
Time: 15:00 - 16:30
Turing Lecture: Building dynamic robots
Tuesday 22 Sep 2020
Time: 15:00 - 16:30
Reliability and reproducibility in computational science
Friday 24 Jan 2020
Time: 09:30 - 17:00
Mathematics of data
Wednesday 29 May 2019 - Friday 31 May 2019
Time: 10:00 - 17:00
Reinforcement and mean-field games in algorithmic trading
Wednesday 27 Mar 2019
Time: 14:00 - 16:00
Turing Lecture: Be prepared to show your working!
Tuesday 11 Dec 2018
Time: 18:15 - 20:30
Computational Semantics Evaluation: The Origins of Senseval and Evolution of SemEval
Monday 16 Jul 2018
Time: 10:30 - 12:00
Impact stories
Revealing hidden details of the ocean floor
An algorithm that automatically detects and classifies marine creatures called sea pens
A new age of Arctic science discovery
Applying algorithms to the fight against global warming. IceNet shortlisted for the Frederik Paulsen Arctic Academic Action Award 2023
Reducing the carbon footprint of the shipping industry
An algorithm that lowers ships’ greenhouse gas emissions by planning the most fuel-efficient route through the waves
Co-designing computing
High-performance computing (HPC) environments such as data centres can be ill-equipped to deal with data science tasks, so Turing researchers collaborated with Intel to co-design better architecture for their HPC systems
Understanding urban air quality
Turing researchers are working with the Greater London Authority to use machine learning and statistical methodology to better analyse air pollution sensor data, design better policy interventions, and improve urban quality of life
Interest groups
People
Kaiwen Zuo
Enrichment Student
Fangru Lin
Enrichment Student
Calum Pennington
Enrichment Student
Haoyu You
Enrichment Student
Yorgos Felekis
Enrichment Student
Xuhui Lin
Enrichment Student
Erin Quan
Enrichment Student
Sushant Gautam
Enrichment Student