Farzad Hosseini is a Hydrology and AI Research Scientist and a technical consultant at IHCantabria, with expertise in deep learning, time-series prediction, and data-driven modelling for hydrology, Earth sciences, and water-related applications. His work focuses on the development and application of artificial intelligence methods for prediction, forecasting, uncertainty analysis, and decision support in environmental and water systems.

 

He completed his PhD at the Universidad de Cantabria, where his research focused on optimized deep neural networks, particularly Long Short-Term Memory networks, for regional rainfall–runoff modelling and streamflow prediction. His research combines advanced AI techniques with hydrological knowledge to improve the accuracy, robustness, and interpretability of predictive AI models in complex environmental systems.

 

At IHCantabria, he contributes to research and consultancy activities involving artificial intelligence, machine learning, hydrological modelling, and predictive analytics, supporting the development of innovative solutions for water resources, environmental management, and Earth-system applications.