We perform fundamental and applied research in the area of Data Science, Machine Learning and Artificial Intelligence (AI). This ranges from better understanding the neuroscience of the human brain, to advancing the state-of-the-art in Machine Learning and AI, and solving real-world problems across a number of application domains.
The majority of our work is cross-disciplinary, collaborating with domain experts within and outside the university. We believe in solving problems that matter and have a keen interest in collaborating with external organisations from both industry and academia.
We work confidently with a wide range of application domains, including health, finance and smart cities. Our technical expertise lies in doing clever things with data, such as machine learning, deep learning, data mining, forecasting, computational intelligence, search & optimisation, simulation modelling, complex networks and human-machine networks.
We solve real-world problems and advance the state-of-the-art in data science and AI. A selection of our portfolio can be found below.
Efficient spinal assessment through AI
Novel AI solutions for law enforcement
Shoeprint analysis to aid law enforcement
Mobile app for automated thyroid drug titration
Events and activity
Deep Learning Winter School
We are hosting the 8th International School on Deep Learning, 16 - 20th January 2023.
Information and registration details can be found on the Deep Learn 2023 website
Innovations in Digital Health and Wellbeing
In collaboration with Frontiers in Big Data, (CiteScore: 2.7), Dr Vegard Engen is co-editing a new article collection (Research Topic) titled: “Innovations in Digital Health and Wellbeing”.
The aim of the Research Topic is to bring together the latest quality articles from researchers working in the area of Digital Health and Wellbeing, focused on either the operational aspects of patient care (e.g. through supply and demand forecasting, discharge prediction and estimating risk of readmissions), or improving treatment and patient care, both on-premise and home or virtual care (using state-of-the-art technologies involving, e.g., Big Data Processing, Visual Analytics, Data Science / Machine Learning, IoT or HCI methods).
Find out more on the Frontiers website