UNIVERSITY OF ICELAND
Understanding flow.
Advancing energy.
Enabling intelligence.
Fluid Dynamics, Energy & Intelligent Computing
Experimental insight, computational modeling and intelligent methods for complex fluid and energy systems.
EXPERIMENT · SIMULATE · LEARN
Where fluid physics meets intelligent computing
Hassanian Lab, led by Dr. Reza Hassanian at the University of Iceland, connects experimental turbulence research with numerical modeling, artificial intelligence and high-performance computing.
01 / Fluid dynamics
Experimental turbulence, computational fluid dynamics and Lagrangian particle tracking.
02 / Energy systems
Wind and solar energy, turbomachinery, heat transfer and numerical modeling.
03 / Intelligent computing
Physics-informed learning, advanced control and high-performance computing.
FEATURED PROJECTS
From fundamental flow to engineering applications
DP4PL
Data-driven and physics-informed learning techniques for particle-laden turbulent flow.
Dr. Hassanian’s role: Principal Investigator
Wind & energy forecasting
Wind speed forecasting, turbine power under leading-edge erosion, and remote sensing data.
Dr. Hassanian’s role: Lead and researcher
PEOPLE
Led by curiosity. Grounded in physics.
Dr. Reza Hassanian
PI · Research Fellow · University of Iceland
Research experience spans industrial power and turbomachinery, fluid mechanics, numerical methods, AI and HPC.
RECENT PUBLICATIONS
Research in print
Reza Hassanian, Gabriele Cavallaro, Ásdís Helgadóttir, Olafur Petur Palsson, Jon Atli Benediktsson, Morris Riedel, “A Decomposition-Based Sequential Deep Learning Model for Time Series Forecasting: SSD-GRU for Wind Data”, Energy and AI, Art. no. 100858, 2026. https://doi.org/10.1016/j.egyai.2026.100858
Reza Hassanian, “Proper Orthogonal Decomposition Analysis of Turbulent Energy Spectra within a Lagrangian Particle Tracking Framework”, Journal of Applied and Computational Mechanics, Article in Press, 2025. https://doi.org/10.22055/jacm.2025.48733.5459
Reza Hassanian, Ásdís Helgadóttir, Farshad Gharibi, Andrea Beck, Morris Riedel. “Data-Driven Deep Learning Models in Particle-Laden Turbulent Flow”, Physics of Fluids, 2025; 37 (2): 023348. https://doi.org/10.1063/5.0251765
Connect with Hassanian Lab
Research enquiries and academic collaboration
University of Iceland · Gróska, Room 318, 3rd floor · 102 Reykjavík, Iceland