Fahimeh Hadavimoghaddam

1.4k total citations
65 papers, 1.0k citations indexed

About

Fahimeh Hadavimoghaddam is a scholar working on Mechanical Engineering, Biomedical Engineering and Ocean Engineering. According to data from OpenAlex, Fahimeh Hadavimoghaddam has authored 65 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Mechanical Engineering, 21 papers in Biomedical Engineering and 20 papers in Ocean Engineering. Recurrent topics in Fahimeh Hadavimoghaddam's work include Hydrocarbon exploration and reservoir analysis (15 papers), Hydraulic Fracturing and Reservoir Analysis (11 papers) and Enhanced Oil Recovery Techniques (11 papers). Fahimeh Hadavimoghaddam is often cited by papers focused on Hydrocarbon exploration and reservoir analysis (15 papers), Hydraulic Fracturing and Reservoir Analysis (11 papers) and Enhanced Oil Recovery Techniques (11 papers). Fahimeh Hadavimoghaddam collaborates with scholars based in China, Iran and Russia. Fahimeh Hadavimoghaddam's co-authors include Abdolhossein Hemmati‐Sarapardeh, Saeid Atashrouz, Ahmad Mohaddespour, Jafar Abdi, Masoud Hadipoor, Mohammad-Reza Mohammadi, Bo Liu, Mehdi Ostadhassan, Ali Abedi and Aydin Larestani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Materials Chemistry A.

In The Last Decade

Fahimeh Hadavimoghaddam

60 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fahimeh Hadavimoghaddam China 20 345 297 280 263 156 65 1.0k
Adel Najafi‐Marghmaleki Iran 22 376 1.1× 430 1.4× 284 1.0× 366 1.4× 85 0.5× 54 1.1k
Ali Barati‐Harooni Iran 21 343 1.0× 361 1.2× 244 0.9× 377 1.4× 79 0.5× 44 993
Reza Soleimani Iran 19 367 1.1× 195 0.7× 143 0.5× 408 1.6× 122 0.8× 33 1.1k
Mohammad-Reza Mohammadi Iran 19 323 0.9× 367 1.2× 329 1.2× 226 0.9× 52 0.3× 45 856
Ram R. Ratnakar United States 22 575 1.7× 600 2.0× 315 1.1× 361 1.4× 329 2.1× 78 1.6k
Cunqi Jia United States 16 428 1.2× 437 1.5× 218 0.8× 73 0.3× 241 1.5× 42 1.1k
Ehsan Heidaryan Iran 23 650 1.9× 357 1.2× 378 1.4× 551 2.1× 74 0.5× 46 1.4k
Saeid Atashrouz Iran 23 414 1.2× 189 0.6× 156 0.6× 601 2.3× 264 1.7× 70 1.4k
Abbas Naderifar Iran 16 215 0.6× 210 0.7× 132 0.5× 135 0.5× 117 0.8× 64 809

Countries citing papers authored by Fahimeh Hadavimoghaddam

Since Specialization
Citations

This map shows the geographic impact of Fahimeh Hadavimoghaddam'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 Fahimeh Hadavimoghaddam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fahimeh Hadavimoghaddam more than expected).

Fields of papers citing papers by Fahimeh Hadavimoghaddam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fahimeh Hadavimoghaddam. 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 Fahimeh Hadavimoghaddam. The network helps show where Fahimeh Hadavimoghaddam may publish in the future.

Co-authorship network of co-authors of Fahimeh Hadavimoghaddam

This figure shows the co-authorship network connecting the top 25 collaborators of Fahimeh Hadavimoghaddam. A scholar is included among the top collaborators of Fahimeh Hadavimoghaddam 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 Fahimeh Hadavimoghaddam. Fahimeh Hadavimoghaddam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Abdi-Khanghah, Mahdi, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.. (2025). Toward predicting CO2 loading capacity in monoethanolamine (MEA) aqueous solutions using deep belief network. Digital Chemical Engineering. 15. 100235–100235. 3 indexed citations
2.
Hadavimoghaddam, Fahimeh, Saeid Atashrouz, Saptarshi Kar, et al.. (2025). Innovative mathematical correlations for estimating mono-nanofluids' density: Insights from white-box machine learning. Results in Physics. 73. 108248–108248.
3.
4.
Mohammadi, Mohammad-Reza, Zhaomin Li, Fahimeh Hadavimoghaddam, et al.. (2025). Enhancing predictions of coal strength variations induced by CO2 exposure through advanced deep learning and machine learning techniques. Fuel. 407. 137210–137210.
5.
Khan, Qaiser uz Zaman, et al.. (2025). Machine Learning Prediction of CO2 Diffusion in Brine: Model Development and Salinity Influence Under Reservoir Conditions. Applied Sciences. 15(15). 8536–8536. 7 indexed citations
6.
Wei, Jianguang, et al.. (2024). Characterization of pore structures after ASP flooding for post-EOR. Energy. 300. 131511–131511. 1 indexed citations
7.
Atashrouz, Saeid, et al.. (2024). On the evaluating membrane flux of forward osmosis systems: Data assessment and advanced intelligent modeling. Water Environment Research. 96(1). e10960–e10960. 1 indexed citations
8.
Lv, Qichao, Haimin Zheng, Xiaochen Li, et al.. (2024). On the Evaluation of Coal Strength Alteration Induced by CO2 Injection Using Advanced Black-Box and White-Box Machine Learning Algorithms. SPE Journal. 29(3). 1672–1691. 8 indexed citations
9.
Lv, Qichao, Tongke Zhou, Haimin Zheng, et al.. (2024). Modeling hydrogen solubility in water: Comparison of adaptive boosting support vector regression, gene expression programming, and cubic equations of state. International Journal of Hydrogen Energy. 57. 637–650. 24 indexed citations
10.
Hadavimoghaddam, Fahimeh, et al.. (2023). Application of advanced correlative approaches to modeling hydrogen solubility in hydrocarbon fuels. International Journal of Hydrogen Energy. 48(51). 19564–19579. 14 indexed citations
11.
Hadavimoghaddam, Fahimeh, et al.. (2023). Modeling gypsum (calcium sulfate dihydrate) solubility in aqueous electrolyte solutions using extreme learning machine. Journal of Water Process Engineering. 57. 104664–104664. 11 indexed citations
12.
Zhao, Li‐Dong, et al.. (2023). Modeling Permeability Using Advanced White-Box Machine Learning Technique: Application to a Heterogeneous Carbonate Reservoir. ACS Omega. 8(25). 22922–22933. 7 indexed citations
13.
Mohammadian, Erfan, et al.. (2023). RNN-based CO2 minimum miscibility pressure (MMP) estimation for EOR and CCUS applications. Fuel. 360. 130598–130598. 14 indexed citations
14.
15.
Atashrouz, Saeid, et al.. (2023). Modeling of H2S solubility in ionic liquids: comparison of white-box machine learning, deep learning and ensemble learning approaches. Scientific Reports. 13(1). 7946–7946. 15 indexed citations
16.
Hadavimoghaddam, Fahimeh, et al.. (2023). Employing ensemble learning techniques for modeling nanofluids' specific heat capacity. International Communications in Heat and Mass Transfer. 143. 106684–106684. 21 indexed citations
17.
Mehrabi-Kalajahi, Seyedsaeed, Ahmad Ostovari Moghaddam, Fahimeh Hadavimoghaddam, et al.. (2022). Entropy-stabilized metal oxide nanoparticles supported on reduced graphene oxide as a highly active heterogeneous catalyst for selective and solvent-free oxidation of toluene: a combined experimental and numerical investigation. Journal of Materials Chemistry A. 10(27). 14488–14500. 22 indexed citations
18.
Abdi, Jafar, Fahimeh Hadavimoghaddam, Masoud Hadipoor, & Abdolhossein Hemmati‐Sarapardeh. (2021). Modeling of CO2 adsorption capacity by porous metal organic frameworks using advanced decision tree-based models. Scientific Reports. 11(1). 24468–24468. 72 indexed citations
19.
Abdi, Jafar, Masoud Hadipoor, Fahimeh Hadavimoghaddam, & Abdolhossein Hemmati‐Sarapardeh. (2021). Estimation of tetracycline antibiotic photodegradation from wastewater by heterogeneous metal-organic frameworks photocatalysts. Chemosphere. 287(Pt 2). 132135–132135. 73 indexed citations
20.
Larestani, Aydin, et al.. (2021). Predicting formation damage of oil fields due to mineral scaling during water-flooding operations: Gradient boosting decision tree and cascade-forward back-propagation network. Journal of Petroleum Science and Engineering. 208. 109315–109315. 47 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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