Reliability and reproducibility in computational science
Friday 24 Jan 2020
Time: 09:30 - 17:00
Search
Software framework development
Open source challenges in the enterprise
Thursday 04 Jul 2019
Time: 17:30 - 19:00
Software Citation
Monday 13 May 2019 - Tuesday 14 May 2019
Time: 13:00 - 16:30
Projects
Scivision
The Scivision project aims to connect computer vision model developers to image data providers from diverse scientific fields.
Quantitative Urban ANalyTics (QUANT)
A land use transportation model simulating the location of employment, population and transport interactions
Ground truth for mental health data science
Linking digital footprint data in the UK birth cohorts to guide the next generation of algorithms for mental health and wellbeing research
Project Odysseus – Understanding London ‘busyness’ and exiting lockdown
Capturing activity over London to better understand 'busyness' and aid effective policy-making strategies for exiting the pandemic lockdown
Digital twins for multiphase flow systems
Integrating data, physics and machine learning to develop rapid predictive models for engineered multiphase flow systems
AI for control problems
Using a competition platform to accelerate progress in data-driven control problems
Synthetic population estimation and scenario projection
Producing high resolution population projections and a framework for exploring future scenarios
Programmes
Publications and software
AI Assistants: A Framework for Semi-Automated Data Wrangling
Data wrangling tasks such as obtaining and linking data from various sources, transforming data...
Petricek, Tomas; van den Burg, Gerrit J. J.; Nazábal, Alfredo; Ceritli, Taha; Jiménez-Ruiz, Ernesto; Williams, Christopher K. I. "AI Assistants: A Framework for Semi-Automated Data Wrangling". IEEE Transactions on Knowledge and Data Engineering 2022
Articles
Events
Reliability and reproducibility in computational science
Friday 24 Jan 2020
Time: 09:30 - 17:00
Open source challenges in the enterprise
Thursday 04 Jul 2019
Time: 17:30 - 19:00
Software Citation
Monday 13 May 2019 - Tuesday 14 May 2019
Time: 13:00 - 16:30
Impact stories
Helping London to navigate lockdown safely
Project Odysseus monitors activity on the streets of London, allowing authorities to make interventions to keep people socially distanced
A machine learning revolution in disaster response
Turing researchers have combined crowd-sourcing, machine learning and neural networks to rapidly reveal the many dimensions of natural disasters, deploying the technology in the aftermath of Hurricane Dorian
Interest groups
People
Tom Savage
Enrichment Student
Lars Henry Berge Olsen
Enrichment Student
Anastasiia Grishina
Enrichment student
Lucy Killoran
Enrichment Student
Andrei-Leonard Nicusan
Enrichment Student
Everlyn Kamau
Enrichment Student
