Projects per year
The Centre of Data Innovation Research (CoDIR) is a new research centre that combines data science and machine learning expertise from astrophysics and computer science, particularly biocomputation. Within the Centre for Astrophysics Research (CAR) we perform world-leading research spanning the discovery of exoplanets, the nature of star formation within our Milky Way and the formation and evolution of galaxies. Computational neuroscience and machine learning, a focus of the Biocomputation Research Group in the Centre for Computer Science and Informatics Research (CCSIR), are thriving areas of interdisciplinary research at the interface between computer science, mathematics and biology. The approach taken by the Biocomputation group is unique as it combines, in addition to computational modelling and mathematical analyses, cutting-edge work in neuromorphic computing, neural data analysis and machine learning.
We have come to recognise that many difficult problems in both fields can be tackled by the same techniques of data analysis and machine learning. Moreover, it is clear that techniques developed for the benefit of what seems to be a highly specific problem in one field can be productively deployed to solve seemingly unrelated problems in another. The objective of CoDIR is to pioneer innovative data science techniques – in particular exploiting expertise in statistics, image analysis, machine learning and computational neuroscience – to develop a strategy to translate these techniques beyond fundamental research, such as medicine, defence and agritech. By embedding this translational approach in our research programme, which has the potential to deliver genuine impact, we seek to become an exemplar research centre that will serve as a blueprint for others aiming to deliver economic and societal impact from blue skies research.
Collaborations and top research areas from the last five years
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1/04/23 → …
GRAVIEW: Predicting gravitational wave background: A holistic, systematic approach to multi-messenger view of massive black hole mergers
1/01/25 → 31/12/30
Yaqoob, M., Steuber, V. & Wróbel, B., 17 Nov 2023, In: BioRxiv. p. 1-14 14 p.
Research output: Contribution to journal › ArticleOpen AccessFile4 Downloads (Pure)
Coil, A., Perrotta, S., Rupke, D., Lochhaas, C., Tremonti, C., Diamond-Stanic, A., Fielding, D., Geach, J., Hickox, R., Moustakas, J., Rudnick, G., Sell, P. & Whalen, K., 16 Oct 2023, (Accepted/In press) In: Nature.
Research output: Contribution to journal › Article › peer-review
Geach, J., Lopez Rodriguez, E., Doherty, M. J., Chen, J., Ivison, R. J., Bendo, G. J., Dye, S. & Coppin, K., 6 Sept 2023, (E-pub ahead of print) In: Nature.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile