Rigas, Georgios

1. An empirical mean-field model of symmetry-breaking in a turbulent wake
   2021/05/28 by Jared Callaham, George Rigas, Callaham, Jared L. +5 · 5 citations
   Engineering · Environmental Science · #Fluid Dynamics and Vibration Analysis #Aerodynamics and Fluid Dynamics Research #Wind and Air Flow Studies
2. Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder
   2023/10/16 by Priyam Gupta, Peter J. Schmid, Gupta, Priyam +7 · 7 citations
   Computer Science · #Anomaly Detection Techniques and Applications #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Human Pose and Action Recognition #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML)
3. Active Flow Control for Bluff Body Drag Reduction Using Reinforcement Learning with Partial Measurements
   2023/07/24 by Chengwei Xia, Junjie Zhang, Xia, Chengwei +5 · 7 citations
   Engineering · #Aerodynamics and Fluid Dynamics Research #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Plasma and Flow Control in Aerodynamics
4. Turbulence model augmented physics informed neural networks for mean flow reconstruction
   2023/06/01 by Yusuf Patel, Vincent Mons, Patel, Yusuf +5 · 5 citations
   Engineering · Environmental Science · Physics and Astronomy · #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks #Plant Water Relations and Carbon Dynamics
5. Efficient global resolvent analysis via the one-way Navier-Stokes equations. Part 2. Optimal response
   2021/11/17 by George Rigas, Rigas, Georgios, Omar Kamal +5 · 4 citations
   Engineering · Physics and Astronomy · #Computational Fluid Dynamics and Aerodynamics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks
6. Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems
   2022/10/31 by Kelshaw, Daniel, Rigas, Georgios, Magri, Luca · 2 citations
   #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG)
7. Machine learning in fluid dynamics: A critical assessment
   2025/08/19 by Taira, Kunihiko, Rigas, Georgios, Fukami, Kai · 4 citations
   #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn)
8. Data-assimilated model-informed reinforcement learning
   2025/06/02 by Ozan, Defne E., Nóvoa, Andrea, Rigas, Georgios +1 · 2 citations
   #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Systems and Control (eess.SY) #electronic engineering #information engineering