Projects per year
Organization profile
Organisation profile
The Centre for Mathematics and Algorithms for Data (MAD) at the University of Bath is an interdisciplinary group of researchers working at the intersection of Statistics, Machine Learning and Numerical Analysis with a huge range of application areas. Data Scientists use mathematics and computation to extract useful information from data. MAD aims to facilitate dialogue between groups, especially theorists in computer science and mathematics, and develop rigour in the field.
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Dive into the research topics where Centre for Mathematics and Algorithms for Data (MAD) is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
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Profiles
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Neill Campbell
- Department of Computer Science - Reader
- Centre for the Analysis of Motion, Entertainment Research & Applications
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- UKRI CDT in Accountable, Responsible and Transparent AI
- Centre for Autonomous Robotics (CENTAUR)
- Centre for Mathematics and Algorithms for Data (MAD)
Person: Research & Teaching
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PaNanoMRI - Early detection of pre-malignant pancreatic cancer using targeted nanoparticles for MRI
1/06/21 → 31/05/22
Project: Research council
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EDPan: Earlier detection of Pancreatic cancer through personalised assessment of risk combined with non-invasive infrared spectroscopy
1/06/21 → 31/05/22
Project: Research council
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Development of wearable technology and innovative methods for the estimation of musculo-skeletal loads and the prevention of injury in running
Preatoni, E., Chen, X., Cazzola, D. & Trewartha, G.
29/03/21 → 26/03/24
Project: UK industry
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(An overview of) Synergistic reconstruction for multimodality/multichannel imaging methods
Arridge, S. R., Ehrhardt, M. J. & Thielemans, K., 28 Jun 2021, In: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences. 379, 2200, p. 20200205Research output: Contribution to journal › Article › peer-review
Open AccessFile1 Citation (Scopus)40 Downloads (Pure) -
Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging
Pirkl, C. M., Nunez-Gonzalez, L., Kofler, F., Endt, S., Grundl, L., Golbabaee, M., Gomez, P. & al, E., 2021, In: Neuroradiology.Research output: Contribution to journal › Article › peer-review
Open Access -
A comparative study about data structures used for efficient management of voxelised full-waveform airborne lidar data during 3d polygonal model creation
Miltiadou, M., Campbell, N. D. F., Cosker, D. & Grant, M. G., 4 Feb 2021, In: Remote Sensing. 13, 4, p. 1-19 19 p., 559.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (Scopus)
Datasets
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Dataset for "Comparison of the within-reader and inter-vendor agreement of left ventricular circumferential strains and volume indices derived from cardiovascular magnetic resonance imaging"
Cookson, A. (Creator), Odunmbaku-Mansell, D. (Creator), Fraser, K. (Creator), Gill, R. (Creator), Raimondo, A. (Creator), Domenico, B. (Creator), Frank, E. (Contributor), Kelly, N. (Contributor), Agostinho Hernandez, B. (Contributor), Fletcher, J. (Contributor), Bartlett, J. (Contributor), Sammut, E. (Contributor), Johnson, T. (Contributor) & Chiribiri, A. (Contributor), University of Bath, 15 Dec 2020
DOI: 10.15125/BATH-00890
Dataset