Hossein Amini

Project: Climate Change and Flooding Risk on the Core Valleys Network of TfW

Hossein joined the group as a PDRA for the TfW project from July 2026, to undertake all research activities proposed for the project including the field measurements, model developments and risk assessment.

Hossein is an Environmental Engineer and Quantitative Modeler specializing in hydrology, freshwater quality, and physics-aware machine learning. His research integrates deep process-based understanding with advanced ML/DL architectures, causal inference, and semi-analytical modeling to tackle complex ecohydrological systems.

With research fellowships in Italy, Germany (IGB Berlin), and the UK, he has built an international track record of interdisciplinary collaboration. In his new position with Coastal Research Group, he is to leverage his quantitative toolkit to develop an independent, innovative research program while contributing to high-quality academic work in water sciences.

Publications

  • Amini, H., Lam, M.Y., Ahmadian, R. (2026). Improved hydro-epidemiological prediction of faecal indicator organisms using knowledge distillation inspired machine learning through dimensionality reduction. Journal of Environmental Management.
  • Amini, H., Lam, M.Y., Yue, Aksoy, A., H., Celebi, E.B., O., Unalan, U.B., Ahmadian, R. (2026). A multi-stage machine-learning approach for lake stratification and turnover prediction. Results in Engineering.
  • Amini, H., Shakeri, R., Ghaderi, N., Fakheri, F., Morovati, K., Zahraei, B., Ahmadian, R. (2026) Explainable machine learning detects water-quality anomalies in the Karkheh River. Scientific Report.