Section page Events from around the Turing Network Conferences, workshops, and other events from around the Turing Network Events from around the Turing Network
The Turing Lectures A series of inspiring talks by leading figures in data science and AI The Turing Lectures
Impact The Turing works with a range of partners with far-reaching, real-world impact across sectors Impact
The Turing Alphabet Introducing the Turing Alphabet: demonstrating the breadth of the Institute. The Turing Alphabet
Research projects Turing Research and Innovation Cluster in Digital Twins Turing Research and Innovation Cluster in Digital Twins
Research projects AI for Numerical Weather Prediction (NWP): AI4NWP Developing artificial intelligence algorithms to fundamentally transform weather forecasting and the prediction of local and global weather events AI for Numerical Weather Prediction (NWP): AI4NWP
Event PhD Connect 2024 Thursday 21 Nov 2024 - Friday 22 Nov 2024 Time: 09:00 - 18:00 Claire Morris Piotr Mirowski Beatriz Costa Gomes Christopher Windows-Yule Alexandros Zenonos Francisco Gomez Medina Mishka Nemes PhD Connect 2024
Research spotlight Premdeep Gill Enrichment student Premdeep Gill is studying Antarctic seals and their sea ice habitats through satellite data, to better understand how they are coping with climate change Premdeep Gill
Research spotlight Erin Young As co-lead of the Turing’s Women in Data Science and AI project, Research Fellow Erin Young’s vital research maps the gendered career trajectories in data science and AI Erin Young
Why work at the Turing? Find out some of the reasons why the Turing is a competitive employer Why work at the Turing?
Data Study Groups Events bringing together some of the country’s top talent from data science, artificial intelligence, and wider fields, to analyse real-world data science challenges Data Study Groups
Partnering with the Turing We work with a wide range of partners to help deliver our mission of changing the world using data science and artificial intelligence Partnering with the Turing
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Reliability and reproducibility in computational science Friday 24 Jan 2020 Time: 09:30 - 17:00 Peter V. Coveney Dan Crommelin Onnie Luk Nick Malleson Anna Nikishova
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
High performance, large-scale regression Investigating the effectiveness of distributed computer systems for running regression analysis, a process which determines the relationships between large numbers of variables
Research Engineering Connecting research to applications, helping create usable and sustainable tools, practices and systems.
Research publications Cross-tier web programming for curated databases: a case study Curated databases have become important sources of information across scientific disciplines, and due to... Cross-tier web programming for curated databases: a case study, Simon Fowler, Simon Harding, Joanna Sharman, and James Cheney. IJDC 16(1), 2021.
Research publications Mixing set and bag semantics The conservativity theorem for nested relational calculus implies that query expressions can freely use... Mixing set and bag semantics, Wilmer Ricciotti and James Cheney, DBPL 2019
Research publications Language-integrated provenance by trace analysis Language-integrated provenance builds on language-integrated query techniques to make provenance information explaining query results... Language-integrated provenance by trace analysis, Stefan Fehrenbach and James Cheney, DBPL 2019
Research publications TryLinks: An interactive tutorial system for a cross-tier Web programming language Links is a web programming language under development in Edinburgh aimed at simplifying web... TryLinks: An interactive tutorial system for a cross-tier Web programming language, Junao Wu, Arek Mikolajczak, and James Cheney, ProWeb 2019
Reliability and reproducibility in computational science Friday 24 Jan 2020 Time: 09:30 - 17:00 Peter V. Coveney Dan Crommelin Onnie Luk Nick Malleson Anna Nikishova
Visualization How can we gain insight into ever-growing datasets and see the reasoning behind automated AI decision-making?