| Physics-informed neural networks for solving Reynolds-averaged Navier–Stokes equations H Eivazi, M Tahani, P Schlatter, R Vinuesa Physics of Fluids 34 (7), 2022 | 199 | 2022 |
| Deep neural networks for nonlinear model order reduction of unsteady flows H Eivazi, H Veisi, MH Naderi, V Esfahanian Physics of Fluids 32 (10), 2020 | 153 | 2020 |
| Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows H Eivazi, S Le Clainche, S Hoyas, R Vinuesa Expert Systems with Applications 202, 117038, 2022 | 96 | 2022 |
| Recurrent neural networks and Koopman-based frameworks for temporal predictions in a low-order model of turbulence H Eivazi, L Guastoni, P Schlatter, H Azizpour, R Vinuesa International Journal of Heat and Fluid Flow 90, 108816, 2021 | 73 | 2021 |
| Physics-informed deep-learning applications to experimental fluid mechanics H Eivazi, Y Wang, R Vinuesa Measurement science and technology 35 (7), 075303, 2024 | 33 | 2024 |
| New method for dynamic mode decomposition of flows over moving structures based on machine learning (hybrid dynamic mode decomposition) MH Naderi, H Eivazi, V Esfahanian Physics of Fluids 31 (12), 2019 | 26 | 2019 |
| Enhancement of PIV measurements via physics-informed neural networks G Hasanuzzaman, H Eivazi, S Merbold, C Egbers, R Vinuesa Measurement Science and Technology 34 (4), 044002, 2023 | 18 | 2023 |
| Sentiment analysis on Twitter data towards climate action E Rosenberg, C Tarazona, F Mallor, H Eivazi, D Pastor-Escuredo, ... Results in Engineering 19, 101287, 2023 | 14 | 2023 |
| The sustainable development goals and aerospace engineering: a critical note through artificial intelligence A Sánchez-Roncero, Ò Garibo-i-Orts, JA Conejero, H Eivazi, F Mallor, ... Results in Engineering 17, 100940, 2023 | 14 | 2023 |
| Analysis and prediction of gas turbine performance with evaporative cooling processes by developing a stage stacking algorithm M Salehi, H Eivazi, M Tahani, M Masdari Journal of cleaner production 277, 122666, 2020 | 14 | 2020 |
| Predicting the temporal dynamics of turbulent channels through deep learning G Borrelli, L Guastoni, H Eivazi, P Schlatter, R Vinuesa International Journal of Heat and Fluid Flow 96, 109010, 2022 | 11 | 2022 |
| The potential of artificial intelligence for achieving healthy and sustainable societies B Sirmaçek, S Gupta, F Mallor, H Azizpour, Y Ban, H Eivazi, H Fang, ... The ethics of artificial intelligence for the sustainable development goals …, 2023 | 9 | 2023 |
| An experimental study on boundary layer transition detection over a pitching supercritical airfoil using hot-film sensors A Tabrizian, M Tatar, M Masdari, H Eivazi, M Seddighi International Journal of Heat and Fluid Flow 86, 108743, 2020 | 8 | 2020 |
| Assessment of turbulence models for transonic oscillating airfoil M Tahani, M Masdari, H Eivazi, M Tatar International Journal of Numerical Methods for Heat & Fluid Flow 27 (11 …, 2017 | 8 | 2017 |
| FE² Computations With Deep Neural Networks: Algorithmic Structure, Data Generation, and Implementation H Eivazi, JA Tröger, S Wittek, S Hartmann, A Rausch Mathematical and Computational Applications 28 (4), 2023 | 5 | 2023 |
| Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks A Jardines, H Eivazi, E Zea, J García-Heras, J Simarro, E Otero, M Soler, ... Expert systems with applications 241, 122466, 2024 | 4 | 2024 |
| Physics-informed transfer learning strategy to accelerate unsteady fluid flow simulations J Jeon, J Lee, H Eivazi, R Vinuesa, SJ Kim arXiv preprint arXiv:2206.06817, 2022 | 3 | 2022 |
| Nonlinear model reduction for operator learning H Eivazi, S Wittek, A Rausch The Second Tiny Papers Track at ICLR 2024, 2024 | 1 | 2024 |
| Efficient integration of deep neural networks in sequential multiscale simulations JA Tröger, H Eivazi, S Hartmann, S Wittek, A Rausch PAMM 23 (4), e202300052, 2023 | 1 | 2023 |
| Enhancing Multiscale Simulations with Constitutive Relations-Aware Deep Operator Networks H Eivazi, M Alikhani, JA Tröger, S Wittek, S Hartmann, A Rausch arXiv preprint arXiv:2405.13759, 2024 | | 2024 |
Ricardo VinuesaAssociate Professor, KTH Royal Institute of Technology在 mech.kth.se 的电子邮件经过验证
