The Data science And Intelligent Systems (DAIS) Research Group are a group of academics, researchers and PhD students within the Division of Computing Science and Mathematics at the University of Stirling. We are interested in the development, theory, and application of data-driven methods to understand, model and optimise the world.
Data is all around us, and humanity generates over 2 quintillion bytes (that’s a 2 followed by 18 zeroes) of new data every day. Cutting-edge techniques are able to make sense of this data and explore it for the greater good. DAIS researchers have embraced data to: inform healthcare decisions through modern statistical analysis; assist those with impairments communicate, using machine learning algorithms to spot c at the momenomplex patterns in sound and brain patterns; predict outcomes of complex systems, with intelligent models that explain their decisions so that they can be trusted; perceive the world through computer vision to assist with sight loss and monitor our environment from space; schedule planes to arrive on time and design buildings to be more comfortable and energy efficient through advanced optimisation methods; and understand how all these techniques work and fit together using novel visualisations methods. These are just some of the areas where our group is advancing knowledge.
We are always happy to talk to companies and other academics about how we might work together. In the first instance please contact Dr Sandy Brownlee (alexander.brownlee@stir.ac.uk), DAIS group leader.
Congratulations to Dr Jason Adair, who is co-lead on a £1.5M grant just awarded entitled “Building effective digital post-hospital discharge and reablement services for older adults in social care: a mixed methods process evaluation using the NASSS framework”. Also this month, members of the DAIS group attended the UKCI conference, hosted by Edinburgh Napier University,
Prof Gabriela Ochoa served as editor-in-chief at this year’s GECCO conference in Malaga, the leading international conference in evolutionary computation. She also co-chaired workshops and tutorials on the topic of landscape analysis. Dr Sandy Brownlee co-chaired the Real World Applications track, as well as the Student and EC & Explainable AI workshops.
Prof Gabriela Ochoa has been awarded a Leverhulme grant worth over £400k in collaboration with Prof Jonathan Fieldsend, University of Exeter for a 3 year study: Under-land: Understanding and Visualising Complex Optimisation. This project aims to develop visualisation and analysis methods to illuminate the interaction between optimisation problems and the algorithms employed to solve them.
This month we welcome Piotr Lipinski and his PhD student Klaudia Balcer, from the University of Wroclaw. They are working with Sandy Brownlee and Giancarlo Catalano on explainability techniques in machine learning and optimisation.