Projects per year
Personal profile
Research interests
- Machine Learning Operations (Governance, Pipelines, Monitoring & Deployment)
- Anomaly and Normality Detection
- Data Engineering (Distribution shift and skew)
- Applied Machine Learning
- Societal Issues (e.g Digital Divide)
Teaching interests
- Machine Learning
- Databases and Data Systems
- Operational Machine Learning
- Ethical, legistlative and societal factors in AI/technology.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Machine Learning, Doctor of Philosophy, Machine Learning methods for the analysis of precipitation patterns
Computer Science, Bachelor of Science, Genetic optimisations for satisfiability and Ramsey theory, University of Plymouth
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Collaborations and top research areas from the last five years
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Projects
- 1 Finished
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Forecasting seasonal to sub-seasonal rainfall in Great Britain using convolutional-neural networks
Barnes, A., McCullen, N. & Kjeldsen, T., 31 Jan 2023, In: Theoretical and Applied Climatology. 151, 1-2, p. 421-432 12 p.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (SciVal) -
Video-Based Convolutional Neural Networks for Rainfall Forecasting
Barnes, A., 5 Jul 2023.Research output: Contribution to conference › Poster › peer-review
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North Atlantic air pressure and temperature conditions associated with heavy rainfall in Great Britain
Barnes, A., Svensson, C. & Kjeldsen, T., 30 Apr 2022, In: International Journal of Climatology. 42, 5, p. 3190-3207 18 p.Research output: Contribution to journal › Article › peer-review
Open Access4 Citations (SciVal) -
Video based convolutional neural networks forecasting for rainfall forecasting
Barnes, A. P., Kjeldsen, T. R. & McCullen, N., 31 Dec 2022, In: IEEE Geoscience and Remote Sensing Letters. 19, 1504605.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (SciVal) -
Identifying and interpreting extreme rainfall events using image classification
Barnes, A., McCullen, N. & Kjeldsen, T., 1 Nov 2021, In: Hydroinformatics. 23, 6, p. 1214–1223Research output: Contribution to journal › Article › peer-review
Open Access
Thesis
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Machine learning methods for the analysis of precipitation patterns: (Alternative Format Thesis)
Author: Barnes, A., 23 Mar 2022Supervisor: Kjeldsen, T. (Supervisor), Prosdocimi, I. (Supervisor) & McCullen, N. (Supervisor)
Student thesis: Doctoral Thesis › PhD
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