UFAZ Hosted Research Seminar on the Application of Machine Learning in Hydrological Processes

On October 24th, the French-Azerbaijani University (UFAZ) hosted a research seminar delivered by Marwan Fahs, Associate Professor at ENGEES (École Nationale du Génie de l’Eau et de l’Environnement de Strasbourg), titled “Machine Learning for Physics-Based Modeling: Applications for Groundwater Flow Simulation.”

Professor Marwan Fahs, a recognized expert in hydrogeology, focuses his research on seawater intrusion in coastal aquifers, CO₂ sequestration in underground formations, and landslide processes, bringing extensive experience in these fields.

During the seminar, Professor Fahs explained how machine learning techniques can be integrated with physics-based models to enhance the simulation and prediction of groundwater flow. He demonstrated how combining data-driven methods with fundamental hydrological principles improves model efficiency, reduces computational costs, and increases the accuracy of results. Practical examples related to groundwater flow and seawater intrusion were presented, highlighting both the potential and challenges of hybrid modeling approaches.

The seminar provided students, researchers, and faculty members with an opportunity to explore research conducted at the intersection of artificial intelligence, machine learning, and hydrogeology.