Behzad Vaferi

3.3k total citations
94 papers, 2.8k citations indexed

About

Behzad Vaferi is a scholar working on Mechanical Engineering, Biomedical Engineering and Ocean Engineering. According to data from OpenAlex, Behzad Vaferi has authored 94 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Mechanical Engineering, 32 papers in Biomedical Engineering and 29 papers in Ocean Engineering. Recurrent topics in Behzad Vaferi's work include Hydraulic Fracturing and Reservoir Analysis (26 papers), Reservoir Engineering and Simulation Methods (17 papers) and Hydrocarbon exploration and reservoir analysis (13 papers). Behzad Vaferi is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (26 papers), Reservoir Engineering and Simulation Methods (17 papers) and Hydrocarbon exploration and reservoir analysis (13 papers). Behzad Vaferi collaborates with scholars based in Iran, Iraq and Qatar. Behzad Vaferi's co-authors include Reza Eslamloueyan, Mostafa Lashkarbolooki, Amith Khandakar, Shahab Ayatollahi, Dariush Mowla, Gholamreza Karimi, Mohsen Karimi, Mohammad Reza Rahimpour, Saleh Hosseini and Parviz Darvishi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Scientific Reports.

In The Last Decade

Behzad Vaferi

92 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Behzad Vaferi Iran 35 1.2k 1.1k 477 310 309 94 2.8k
Hari B. Vuthaluru Australia 37 1.1k 0.9× 1.7k 1.6× 662 1.4× 296 1.0× 283 0.9× 149 3.4k
Alireza Baghban Iran 38 1.3k 1.1× 1.5k 1.4× 598 1.3× 466 1.5× 450 1.5× 147 4.1k
Ali Vatani Iran 32 1.5k 1.3× 569 0.5× 320 0.7× 268 0.9× 471 1.5× 79 2.6k
Xingang Li China 32 675 0.6× 766 0.7× 338 0.7× 418 1.3× 239 0.8× 167 3.0k
Wenli Song China 33 1.1k 0.9× 2.2k 2.0× 420 0.9× 857 2.8× 180 0.6× 145 3.7k
Nima Rezaei Canada 25 931 0.8× 717 0.7× 1.1k 2.4× 366 1.2× 206 0.7× 69 2.8k
Rached Ben‐Mansour Saudi Arabia 33 2.2k 1.8× 1.1k 1.0× 443 0.9× 899 2.9× 515 1.7× 160 4.1k
Esmail M. A. Mokheimer Saudi Arabia 30 1.4k 1.2× 663 0.6× 317 0.7× 450 1.5× 978 3.2× 149 3.5k
Ali Lohi Canada 33 1.1k 0.9× 1.4k 1.3× 1.1k 2.3× 262 0.8× 125 0.4× 161 4.1k
Feridun Esmaeilzadeh Iran 41 1.2k 1.0× 2.4k 2.2× 1.0k 2.2× 727 2.3× 410 1.3× 202 4.8k

Countries citing papers authored by Behzad Vaferi

Since Specialization
Citations

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

Fields of papers citing papers by Behzad Vaferi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Behzad Vaferi

This figure shows the co-authorship network connecting the top 25 collaborators of Behzad Vaferi. A scholar is included among the top collaborators of Behzad Vaferi 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 Behzad Vaferi. Behzad Vaferi 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.
Karimi, Mohsen, Mohammad Shirzad, & Behzad Vaferi. (2025). Employing diverse machine learning approaches to estimate the achievable bio-oil yield from sustainable biomass sources. Sustainable materials and technologies. 47. e01823–e01823.
2.
Mirzaie, Mohammad, Mitra Amani, Nedasadat Saadati Ardestani, & Behzad Vaferi. (2024). Experimental measurement and thermodynamic/intelligent modeling of yellow 2 G solubility in supercritical carbon dioxide with/without co-solvent. Process Safety and Environmental Protection. 207. 160–180. 9 indexed citations
3.
Esmaeili-Faraj, Seyyed Hamid, et al.. (2024). Experimental Measurement and Modeling Analysis of the Heat Transfer in Graphene Oxide/Turbine Oil Non‐Newtonian Nanofluids. Nanomaterials and Nanotechnology. 2024(1). 1 indexed citations
4.
5.
Ahmadi, Yaser, et al.. (2024). Synthesis and application of eucalyptus plant- and walnut shell- CuO/Fe3O4/Xanthan polymeric nanocomposites for enhanced oil recovery in carbonate reservoirs. Journal of Petroleum Exploration and Production Technology. 14(11). 3045–3054. 11 indexed citations
6.
Ahmadi, Yaser, Mohamed Arselene Ayari, Seyyed Hossein Hosseini, et al.. (2023). Application of Green Polymeric Nanocomposites for Enhanced Oil Recovery by Spontaneous Imbibition from Carbonate Reservoirs. Polymers. 15(14). 3064–3064. 24 indexed citations
7.
Azari, Ahmad, et al.. (2023). Investigation of methane and ethane diffusivity in the glass reinforced epoxy composite: Experimental and simulation. Process Safety and Environmental Protection. 180. 1012–1022. 4 indexed citations
8.
Pandey, Rakesh Kumar, et al.. (2023). Applying a deep-learning surrogate model to simulate and compare achievable oil recovery by different waterflood scenarios. Petroleum Science and Technology. 42(25). 4405–4423. 3 indexed citations
9.
Bakhtyari, Ali, Ali Rasoolzadeh, Behzad Vaferi, & Amith Khandakar. (2023). Application of machine learning techniques to the modeling of solubility of sugar alcohols in ionic liquids. Scientific Reports. 13(1). 12161–12161. 8 indexed citations
10.
11.
Hosseini, Saleh, Amith Khandakar, Muhammad E. H. Chowdhury, et al.. (2022). Novel and robust machine learning approach for estimating the fouling factor in heat exchangers. Energy Reports. 8. 8767–8776. 35 indexed citations
12.
Ayari, Mohamed Arselene, Hamidreza Sadeghsalehi, Behzad Vaferi, et al.. (2022). Estimating the Dissolution of Anticancer Drugs in Supercritical Carbon Dioxide with a Stacked Machine Learning Model. Pharmaceutics. 14(8). 1632–1632. 20 indexed citations
13.
Alizadeh, Seyed Mehdi, et al.. (2022). Predicting the hydrogen uptake ability of a wide range of zeolites utilizing supervised machine learning methods. International Journal of Hydrogen Energy. 47(51). 21782–21793. 24 indexed citations
14.
Wang, Jing, Mohamed Arselene Ayari, Amith Khandakar, et al.. (2022). Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies. Polymers. 14(3). 527–527. 39 indexed citations
15.
Pandey, Rakesh Kumar, et al.. (2022). Metaheuristic algorithm integrated neural networks for well-test analyses of petroleum reservoirs. Scientific Reports. 12(1). 16551–16551. 32 indexed citations
16.
Cao, Yan, et al.. (2022). Employing computational fluid dynamics technique for analyzing the PACK-1300XY with methanol and isopropanol mixture. Scientific Reports. 12(1). 6588–6588. 2 indexed citations
17.
18.
Vaferi, Behzad. (2019). Prediction of methanol loss by hydrocarbon gas phase in hydrate inhibition unit by back propagation neural networks. SHILAP Revista de lepidopterología. 5 indexed citations
19.
Vaferi, Behzad, et al.. (2015). Modification and optimization of the industrial methanol production process. 10(2). 3 indexed citations
20.
Lashkarbolooki, Mostafa, Behzad Vaferi, & Dariush Mowla. (2012). Using Artificial Neural Network to Predict the Pressure Drop in a Rotating Packed Bed. Separation Science and Technology. 47(16). 2450–2459. 38 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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