Hamidreza Eivazi

906 total citations · 1 hit paper
18 papers, 547 citations indexed

About

Hamidreza Eivazi is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Hamidreza Eivazi has authored 18 papers receiving a total of 547 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Statistical and Nonlinear Physics, 9 papers in Computational Mechanics and 7 papers in Aerospace Engineering. Recurrent topics in Hamidreza Eivazi's work include Model Reduction and Neural Networks (10 papers), Fluid Dynamics and Turbulent Flows (8 papers) and Fluid Dynamics and Vibration Analysis (3 papers). Hamidreza Eivazi is often cited by papers focused on Model Reduction and Neural Networks (10 papers), Fluid Dynamics and Turbulent Flows (8 papers) and Fluid Dynamics and Vibration Analysis (3 papers). Hamidreza Eivazi collaborates with scholars based in Sweden, Germany and Iran. Hamidreza Eivazi's co-authors include Ricardo Vinuesa, Mojtaba Tahani, Philipp Schlatter, Sergio Hoyas, Soledad Le Clainche, Yuning Wang, Vahid Esfahanian, Christoph Egbers, Mehran Masdari and Francesco Fuso Nerini and has published in prestigious journals such as Journal of Cleaner Production, Expert Systems with Applications and Physics of Fluids.

In The Last Decade

Hamidreza Eivazi

16 papers receiving 531 citations

Hit Papers

Physics-informed neural n... 2022 2026 2023 2024 2022 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Physics-informed neural networks for solving Reynolds-averaged Navier–Stokes equations
    2022 265 citations Hamidreza Eivazi, Mojtaba Tahani et al. Physics of Fluids profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hamidreza Eivazi Sweden 10 340 302 163 81 58 18 547
Zhiwen Deng China 14 231 0.7× 356 1.2× 184 1.1× 80 1.0× 41 0.7× 29 671
Jonathan Viquerat France 13 303 0.9× 357 1.2× 141 0.9× 78 1.0× 50 0.9× 33 640
Nicholas Geneva United States 7 236 0.7× 233 0.8× 70 0.4× 45 0.6× 83 1.4× 7 469
Luca Guastoni Sweden 5 263 0.8× 329 1.1× 110 0.7× 63 0.8× 37 0.6× 12 432
Harshal D. Akolekar Australia 8 166 0.5× 279 0.9× 163 1.0× 64 0.8× 29 0.5× 20 403
Qinghua Jiang Singapore 5 209 0.6× 259 0.9× 173 1.1× 58 0.7× 28 0.5× 5 449
Eric Parish United States 9 404 1.2× 419 1.4× 151 0.9× 60 0.7× 53 0.9× 27 648
Brendan Tracey United States 8 216 0.6× 313 1.0× 161 1.0× 46 0.6× 46 0.8× 12 533
Linyang Zhu China 6 277 0.8× 353 1.2× 191 1.2× 56 0.7× 16 0.3× 11 452
Yiyang Sun United States 8 238 0.7× 443 1.5× 259 1.6× 58 0.7× 16 0.3× 23 549

Countries citing papers authored by Hamidreza Eivazi

Since Specialization
Citations

This map shows the geographic impact of Hamidreza Eivazi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hamidreza Eivazi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hamidreza Eivazi more than expected).

Fields of papers citing papers by Hamidreza Eivazi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hamidreza Eivazi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hamidreza Eivazi. The network helps show where Hamidreza Eivazi may publish in the future.

Co-authorship network of co-authors of Hamidreza Eivazi

This figure shows the co-authorship network connecting the top 25 collaborators of Hamidreza Eivazi. A scholar is included among the top collaborators of Hamidreza Eivazi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hamidreza Eivazi. Hamidreza Eivazi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Eivazi, Hamidreza, et al.. (2025). R2RNet: A deep spatiotemporal RaintoRiverNetwork for water level prediction and flood forecasting. Journal of Hydrology Regional Studies. 61. 102571–102571.
2.
Eivazi, Hamidreza, Yuning Wang, & Ricardo Vinuesa. (2024). Physics-informed deep-learning applications to experimental fluid mechanics. Measurement Science and Technology. 35(7). 75303–75303. 31 indexed citations
3.
Eivazi, Hamidreza, et al.. (2023). Thunderstorm prediction during pre-tactical air-traffic-flow management using convolutional neural networks. Expert Systems with Applications. 241. 122466–122466. 9 indexed citations
4.
Eivazi, Hamidreza, et al.. (2023). FE² Computations With Deep Neural Networks: Algorithmic Structure, Data Generation, and Implementation. SSRN Electronic Journal. 2 indexed citations
5.
6.
Eivazi, Hamidreza, et al.. (2023). FE2 Computations with Deep Neural Networks: Algorithmic Structure, Data Generation, and Implementation. Mathematical and Computational Applications. 28(4). 91–91. 6 indexed citations
7.
Conejero, J. Alberto, Hamidreza Eivazi, Francesco Fuso Nerini, et al.. (2023). The Sustainable Development Goals and Aerospace Engineering: A critical note through Artificial Intelligence. Results in Engineering. 17. 100940–100940. 20 indexed citations
8.
Mallor, Fermín, et al.. (2023). Sentiment analysis on Twitter data towards climate action. Results in Engineering. 19. 101287–101287. 23 indexed citations
9.
Guastoni, Luca, et al.. (2022). Predicting the temporal dynamics of turbulent channels through deep learning. International Journal of Heat and Fluid Flow. 96. 109010–109010. 17 indexed citations
10.
Eivazi, Hamidreza, et al.. (2022). Enhancement of PIV measurements via physics-informed neural networks. Measurement Science and Technology. 34(4). 44002–44002. 29 indexed citations
11.
Eivazi, Hamidreza, Soledad Le Clainche, Sergio Hoyas, & Ricardo Vinuesa. (2022). Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows. Expert Systems with Applications. 202. 117038–117038. 88 indexed citations
12.
Eivazi, Hamidreza, Mojtaba Tahani, Philipp Schlatter, & Ricardo Vinuesa. (2022). Physics-informed neural networks for solving Reynolds-averaged Navier–Stokes equations. Physics of Fluids. 34(7). 265 indexed citations breakdown →
13.
Eivazi, Hamidreza, et al.. (2022). Thunderstorm Prediction During Pre-Tactical Air-Traffic-Flow Management Using Convolutional Neural Networks. SSRN Electronic Journal. 3 indexed citations
14.
Lee, Juhyeong, et al.. (2022). Physics-Informed Transfer Learning Strategy to Accelerate Unsteady Fluid Flow Simulations. SSRN Electronic Journal. 3 indexed citations
15.
Eivazi, Hamidreza, et al.. (2020). Analysis and prediction of gas turbine performance with evaporative cooling processes by developing a stage stacking algorithm. Journal of Cleaner Production. 277. 122666–122666. 9 indexed citations
16.
Masdari, Mehran, et al.. (2020). An experimental study on boundary layer transition detection over a pitching supercritical airfoil using hot-film sensors. International Journal of Heat and Fluid Flow. 86. 108743–108743. 6 indexed citations
17.
18.
Tahani, Mojtaba, et al.. (2017). Assessment of turbulence models for transonic oscillating airfoil. International Journal of Numerical Methods for Heat & Fluid Flow. 27(11). 2603–2628. 8 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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