Serveh Kamrava

1.0k total citations · 1 hit paper
21 papers, 797 citations indexed

About

Serveh Kamrava is a scholar working on Ocean Engineering, Mechanical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Serveh Kamrava has authored 21 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Ocean Engineering, 7 papers in Mechanical Engineering and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Serveh Kamrava's work include Enhanced Oil Recovery Techniques (8 papers), Hydrocarbon exploration and reservoir analysis (4 papers) and Advanced Neural Network Applications (3 papers). Serveh Kamrava is often cited by papers focused on Enhanced Oil Recovery Techniques (8 papers), Hydrocarbon exploration and reservoir analysis (4 papers) and Advanced Neural Network Applications (3 papers). Serveh Kamrava collaborates with scholars based in United States, United Kingdom and China. Serveh Kamrava's co-authors include Pejman Tahmasebi, Muhammad Sahimi, Tao Bai, Fadwa Eljack, Mahmoud M. El‐Halwagi, Kerron J. Gabriel, Felipe P. J. de Barros, Senyou An, Keyu Liu and Yuqi Wu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Acta Materialia and Geophysical Research Letters.

In The Last Decade

Serveh Kamrava

20 papers receiving 784 citations

Hit Papers

align trajectories

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.

Machine learning in geo- and environmental sciences: From small to large scale

2020 210 citations Pejman Tahmasebi, Serveh Kamrava et al. Advances in Water Resources profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Serveh Kamrava United States	15	341	231	204	177	136	21	797
Hui Qin China	19	461 1.4×	141 0.6×	107 0.5×	140 0.8×	104 0.8×	83	1.1k
Daolun Li China	18	590 1.7×	451 2.0×	562 2.8×	169 1.0×	80 0.6×	64	1.1k
Javier E. Santos United States	15	321 0.9×	166 0.7×	228 1.1×	105 0.6×	143 1.1×	57	659
Nanzhe Wang China	16	329 1.0×	62 0.3×	267 1.3×	230 1.3×	108 0.8×	21	796
Heng Li China	16	480 1.4×	99 0.4×	374 1.8×	376 2.1×	169 1.2×	48	1.2k
Ying Da Wang Australia	20	734 2.2×	497 2.2×	522 2.6×	298 1.7×	158 1.2×	46	1.5k
Marina V. Karsanina Russia	18	537 1.6×	554 2.4×	295 1.4×	272 1.5×	108 0.8×	41	1.1k
Sadegh Karimpouli Iran	19	553 1.6×	497 2.2×	457 2.2×	104 0.6×	48 0.4×	37	1.2k
G. A. Ramadass India	16	392 1.1×	343 1.5×	225 1.1×	122 0.7×	32 0.2×	88	987

Countries citing papers authored by Serveh Kamrava

Since Specialization

Citations

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

Fields of papers citing papers by Serveh Kamrava

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Serveh Kamrava

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

All Works

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20 of 20 papers shown

Kamrava, Serveh, et al.. (2026). Integrating molecular dynamics and machine learning to predict hydrogen–brine interfacial tension for subsurface storage. International Journal of Hydrogen Energy. 204. 153347–153347.

Kamrava, Serveh, et al.. (2025). Inverse design of microstructures using conditional continuous normalizing flows. Acta Materialia. 285. 120704–120704. 5 indexed citations

Soltanmohammadi, Ramin, et al.. (2024). Elastic constants from charge density distribution in FCC high-entropy alloys using CNN and DFT. SHILAP Revista de lepidopterología. 2(4). 2 indexed citations

Wu, Yuqi, Senyou An, Pejman Tahmasebi, et al.. (2023). An end-to-end approach to predict physical properties of heterogeneous porous media: Coupling deep learning and physics-based features. Fuel. 352. 128753–128753. 16 indexed citations

Kamrava, Serveh, et al.. (2023). Estimation of internal states in a Li-ion battery using BiLSTM with Bayesian hyperparameter optimization. Journal of Energy Storage. 74. 109522–109522. 19 indexed citations

Wu, Yuqi, Pejman Tahmasebi, Keyu Liu, et al.. (2023). Modeling the physical properties of hydrate‐bearing sediments: Considering the effects of occurrence patterns. Energy. 278. 127674–127674. 22 indexed citations

Kamrava, Serveh, et al.. (2023). Effect of Wettability on Two-Phase Flow Through Granular Porous Media: Fluid Rupture and Mechanics of the Media. Chemical Engineering Science. 269. 118446–118446. 16 indexed citations

Kamrava, Serveh, et al.. (2023). Minireview on Porous Media and Microstructure Reconstruction Using Machine Learning Techniques: Recent Advances and Outlook. Energy & Fuels. 37(20). 15348–15372. 15 indexed citations

Kamrava, Serveh, et al.. (2022). End-to-end three-dimensional designing of complex disordered materials from limited data using machine learning. Physical review. E. 106(5). 55301–55301. 8 indexed citations

10.

Arora, Gaurav, Serveh Kamrava, Pejman Tahmasebi, & Dilpuneet S. Aidhy. (2022). Charge-density based convolutional neural networks for stacking fault energy prediction in concentrated alloys. Materialia. 26. 101620–101620. 7 indexed citations

11.

Kamrava, Serveh, et al.. (2021). Estimating Dispersion Coefficient in Flow Through Heterogeneous Porous Media by a Deep Convolutional Neural Network. Geophysical Research Letters. 48(18). 21 indexed citations

12.

Kamrava, Serveh, Muhammad Sahimi, & Pejman Tahmasebi. (2021). Simulating fluid flow in complex porous materials by integrating the governing equations with deep-layered machines. npj Computational Materials. 7(1). 46 indexed citations

13.

Kamrava, Serveh, Pejman Tahmasebi, & Muhammad Sahimi. (2021). Physics- and image-based prediction of fluid flow and transport in complex porous membranes and materials by deep learning. Journal of Membrane Science. 622. 119050–119050. 41 indexed citations

14.

Kamrava, Serveh, Muhammad Sahimi, & Pejman Tahmasebi. (2020). Quantifying accuracy of stochastic methods of reconstructing complex materials by deep learning. Physical review. E. 101(4). 43301–43301. 23 indexed citations

15.

Tahmasebi, Pejman, Serveh Kamrava, Tao Bai, & Muhammad Sahimi. (2020). Machine learning in geo- and environmental sciences: From small to large scale. Advances in Water Resources. 142. 103619–103619. 210 indexed citations breakdown →

16.

Kamrava, Serveh, Pejman Tahmasebi, & Muhammad Sahimi. (2019). Enhancing images of shale formations by a hybrid stochastic and deep learning algorithm. Neural Networks. 118. 310–320. 83 indexed citations

17.

Tahmasebi, Pejman & Serveh Kamrava. (2019). A pore-scale mathematical modeling of fluid-particle interactions: Thermo-hydro-mechanical coupling. International journal of greenhouse gas control. 83. 245–255. 37 indexed citations

18.

Kamrava, Serveh, Pejman Tahmasebi, & Muhammad Sahimi. (2019). Linking Morphology of Porous Media to Their Macroscopic Permeability by Deep Learning. Transport in Porous Media. 131(2). 427–448. 137 indexed citations

19.

Tahmasebi, Pejman & Serveh Kamrava. (2018). A Multiscale Approach for Geologically and Flow Consistent Modeling. Transport in Porous Media. 124(1). 237–261. 12 indexed citations

20.

Tahmasebi, Pejman & Serveh Kamrava. (2018). Rapid multiscale modeling of flow in porous media. Physical review. E. 98(5). 46 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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