Computational Fluid Dynamics (CFD)
Development and application of numerical methods for solving flow equations, using finite element methods (FEniCSx) and physics-informed neural networks.
The Lab's research spans a wide range of topics that connect fluid mechanics with water resources management and modern scientific computing.
Thematic Pillars
Water Resources Management
Hydrological and hydraulic modelling of catchments, design and optimisation of water management projects, flood phenomena and protection.
Energy Applications
Fluid mechanics for energy systems: hydropower installations, wind energy (aerodynamics), cooling and energy storage systems.
Scientific Machine Learning
Hybrid physics–data models, autonomous Bayesian Optimization frameworks, and agentic systems for scientific computing.
Active Projects
2026 — ACTIVE
Agentic PINN Framework for Multi-physics Problems
Development of a comprehensive framework for solving engineering problems using Physics-Informed Neural Networks and autonomous optimisation agents.
2026 — ACTIVE
2D Flood Simulation with Data-Assisted PINNs
Collaborative project on hybrid modelling of flood events using HEC-RAS as a baseline.