Kontakt
Pfaffenwaldring 5a
70569 Stuttgart
Raum: 1.15
2026
- Wildt N, Callau Medrano S, Riazi M, Oladyshkin S, Nowak W. Deep arbitrary Polynomial Chaos Expansion ODE for Hydrological System Modeling: It is all about that Basis. Bologna, Italy: 26th International Conference on Computational Methods in Water Resources (CMWR); 2026.
2025
- Riazi M, Bateni SM, Jun C, Farooque AA, Khosravi K, Abolfathi S. Enhancing rainfall-runoff simulation in data-poor watersheds: integrating remote sensing and hybrid decomposition for hydrologic modelling. Water Resources Management. 2025;1–26.
2024
- Riazi M, Khosravi K, Samani MR, Han S, Eslamian S. Assessing groundwater drought vulnerability through baseflow separation and index-based analysis under climate change projections. Groundwater for Sustainable Development. 2024;25:101179.
2023
- Riazi M, Khosravi K, Shahedi K, Ahmad S, Jun C, Bateni SM, et al. Enhancing flood susceptibility modeling using multi-temporal SAR images, CHIRPS data, and hybrid machine learning algorithms. Science of The Total Environment. 2023;871:162066.
- Riazi M, Karimi M, Eslamian S, Riahi Samani M. Comparative assessment of advanced machine learning techniques for simulation of lake water level fluctuations based on different dimensionality reduction methods. Earth Science Informatics. 2023;16:37–55.
09/2016 B.Sc. Agricultural Engineering-Water, IKIU, Qazvin, Iran
01/2023 M.Sc. Civil Engineering-Water Resources Management, IAU,
Isfahan, Iran
Seit 10/2025 Doktorand, Institut für Wasser- und Umweltsystemmodellierung,
Universität Stuttgart
Hybride physikalisch informierte Machine/Deep Learning für dynamische Systeme
Unsicherheitsquantifizierung in dynamischen Systemen
Neuronale Netze für die Modellierung dynamischer Systeme
Google Scholar:
https://scholar.google.com/citations?user=ohf7xysAAAAJ&hl=en
ResearchGate:
https://www.researchgate.net/profile/Mostafa-Riazi
Github:
https://mostafariazi.github.io/