Personal profile
Research interests
- AI for Extremes (Flooding, Rainfall, Drought etc.)
- Machine Learning Operations (Governance, Pipelines, Monitoring & Deployment)
- Anomaly and Normality Detection
- Data Engineering (Distribution shift and skew)
- 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.
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
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):
-
SDG 6 Clean Water and Sanitation -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities -
SDG 13 Climate Action
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
Developing rainfall frequency models for critical infrastructure design in a changing environment
Kjeldsen, T. (PI) & Barnes, A. (CoI)
1/08/24 → 31/07/26
Project: Central government, health and local authorities
-
-
Beach monitoring: Do we need to survey to spring low tide?
Rose, S., Blenkinsopp, C., Barnes, A., Russell, W. & Thompson, C., 15 Mar 2026, In: Coastal Engineering. 205, 104911.Research output: Contribution to journal › Article › peer-review
Open Access -
Operational uncertainty in machine-learning based debris block detection in urban waterways
Rowlatt, C., Barnes, A., Dooley, S. & Kjeldsen, T., 2 Mar 2026, (E-pub ahead of print) In: Cambridge Prisms: Water. 4, p. 1-11 11 p.Research output: Contribution to journal › Article › peer-review
Open Access -
The DaTUM framework: a cross-sector thematic analysis of data quality dimensions and their impacting factors
Smallwood, E., Burke, R., Barnes, A. P. & Ivarson, M., 30 Jun 2026, In: International Journal of Information Management Data Insights. 6, 1, 100407.Research output: Contribution to journal › Article › peer-review
Open AccessFile8 Downloads (Pure) -
A Convolutional Neural Network for the Detection of Gravity Waves in Satellite Observations and Numerical Simulations
Okui , H., Wright, C., Berthelemy, P. G., Hindley, N. P., Hoffmann, L. & Barnes, A. P., 16 Jun 2025, In: Geophysical Research Letters. 52, 11, e2025GL115683.Research output: Contribution to journal › Article › peer-review
Open Access2 Link opens in a new tab Citations (SciVal) -
Automated Classification of Vocalisations from Wild and Captive Seal Populations
Butler, W., Smith, H., Lloyd, W., Impraimakis, M., Barnes, A. & Hunter, A. J., 20 Jun 2025.Research output: Contribution to conference › Paper
Thesis
-
Machine learning methods for the analysis of precipitation patterns: (Alternative Format Thesis)
Barnes, A. (Author), Kjeldsen, T. (Supervisor), Prosdocimi, I. (Supervisor) & McCullen, N. (Supervisor), 23 Mar 2022Student thesis: Doctoral Thesis › PhD
File
Prizes
-
Most Engaging Lecturer (Meme Supreme)
Barnes, A. (Recipient), 2024
Prize: Prize (including medals and awards)
-
Mary Tasker (Teaching Excellence)
Barnes, A. (Nominee), 2024
Prize: Prize (including medals and awards)
-
Royal Agricultural University
Barnes, A. (Visiting lecturer)
1 Feb 2024 → …Activity: Visiting an external academic institution › Visiting lecturer
-
Radio Interview: AI on the river
Barnes, A. (Interviewee)
9 Oct 2024Activity: Media article or participation, blog › Media article or participation