Ehsan Sadrossadat

724 total citations
17 papers, 592 citations indexed

About

Ehsan Sadrossadat is a scholar working on Civil and Structural Engineering, Building and Construction and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Ehsan Sadrossadat has authored 17 papers receiving a total of 592 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Civil and Structural Engineering, 7 papers in Building and Construction and 6 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Ehsan Sadrossadat's work include Geotechnical Engineering and Analysis (6 papers), Dam Engineering and Safety (5 papers) and Geotechnical Engineering and Underground Structures (5 papers). Ehsan Sadrossadat is often cited by papers focused on Geotechnical Engineering and Analysis (6 papers), Dam Engineering and Safety (5 papers) and Geotechnical Engineering and Underground Structures (5 papers). Ehsan Sadrossadat collaborates with scholars based in Iran, Australia and Norway. Ehsan Sadrossadat's co-authors include Behnam Ghorbani, Hakan Başarır, Amir H. Alavi, Mohamed Elchalakani, Ali Karrech, Jafar Bolouri Bazaz, Danial Mohammadzadeh S., Tanvir Ahmed, Bo Yang and Andy Fourie and has published in prestigious journals such as Construction and Building Materials, International Journal of Rock Mechanics and Mining Sciences and Minerals Engineering.

In The Last Decade

Ehsan Sadrossadat

17 papers receiving 589 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ehsan Sadrossadat Iran 14 536 169 132 73 58 17 592
Dmitrii Vladimirovich Ulrikh Russia 14 425 0.8× 149 0.9× 64 0.5× 138 1.9× 121 2.1× 42 620
Primož Jelušič Slovenia 12 205 0.4× 78 0.5× 95 0.7× 31 0.4× 57 1.0× 41 308
Tuan Anh Pham Vietnam 9 326 0.6× 55 0.3× 122 0.9× 27 0.4× 43 0.7× 19 440
Hadi Hasanzadehshooiili Iran 13 442 0.8× 66 0.4× 150 1.1× 103 1.4× 36 0.6× 23 504
Duncan Nicholson United Kingdom 13 276 0.5× 112 0.7× 92 0.7× 31 0.4× 75 1.3× 32 486
Bojan Žlender Slovenia 12 173 0.3× 68 0.4× 96 0.7× 26 0.4× 71 1.2× 37 366
Muzamir Hasan Malaysia 15 564 1.1× 68 0.4× 65 0.5× 17 0.2× 50 0.9× 73 710
Xianghui Deng China 11 368 0.7× 103 0.6× 156 1.2× 138 1.9× 22 0.4× 36 521
Ge Li China 10 368 0.7× 46 0.3× 159 1.2× 91 1.2× 35 0.6× 24 431
Xuyang Shi China 10 233 0.4× 80 0.5× 44 0.3× 122 1.7× 67 1.2× 25 348

Countries citing papers authored by Ehsan Sadrossadat

Since Specialization
Citations

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

Fields of papers citing papers by Ehsan Sadrossadat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ehsan Sadrossadat

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

All Works

17 of 17 papers shown
1.
Sadrossadat, Ehsan, Hakan Başarır, Ali Karrech, & Mohamed Elchalakani. (2022). Innovative AI-based multi-objective mixture design optimisation of CPB considering properties of tailings and cement. International Journal of Mining Reclamation and Environment. 37(2). 110–126. 6 indexed citations
2.
Sadrossadat, Ehsan, Hakan Başarır, Ali Karrech, & Mohamed Elchalakani. (2022). An engineered ML model for prediction of the compressive strength of Eco-SCC based on type and proportions of materials. Cleaner Materials. 4. 100072–100072. 9 indexed citations
3.
Sadrossadat, Ehsan, Hakan Başarır, Ali Karrech, & Mohamed Elchalakani. (2021). Multi-objective mixture design and optimisation of steel fiber reinforced UHPC using machine learning algorithms and metaheuristics. Engineering With Computers. 38(S3). 2569–2582. 58 indexed citations
4.
Ahmed, Tanvir, Mohamed Elchalakani, Hakan Başarır, et al.. (2021). Development of ECO-UHPC utilizing gold mine tailings as quartz sand alternative. Cleaner Engineering and Technology. 4. 100176–100176. 59 indexed citations
5.
Sadrossadat, Ehsan, et al.. (2020). Multi-objective mixture design of cemented paste backfill using particle swarm optimisation algorithm. Minerals Engineering. 153. 106385–106385. 50 indexed citations
6.
Sadrossadat, Ehsan & Hakan Başarır. (2019). An Evolutionary-Based Prediction Model of the 28-Day Compressive Strength of High-Performance Concrete Containing Cementitious Materials. Advances in Civil Engineering Materials. 8(3). 484–497. 14 indexed citations
7.
Sadrossadat, Ehsan, et al.. (2018). New empirical formulations for indirect estimation of peak-confined compressive strength and strain of circular RC columns using LGP method. Engineering With Computers. 34(4). 865–880. 16 indexed citations
8.
Sadrossadat, Ehsan, et al.. (2018). Predictive modelling of the MR of subgrade cohesive soils incorporating CPT-related parameters through a soft-computing approach. Road Materials and Pavement Design. 21(3). 701–719. 13 indexed citations
9.
Ghorbani, Behnam, et al.. (2018). Numerical ANFIS-Based Formulation for Prediction of the Ultimate Axial Load Bearing Capacity of Piles Through CPT Data. Geotechnical and Geological Engineering. 36(4). 2057–2076. 37 indexed citations
10.
Sadrossadat, Ehsan, et al.. (2018). Use of adaptive neuro-fuzzy inference system and gene expression programming methods for estimation of the bearing capacity of rock foundations. Engineering Computations. 35(5). 2078–2106. 27 indexed citations
11.
12.
Sadrossadat, Ehsan, et al.. (2016). Towards application of linear genetic programming for indirect estimation of the resilient modulus of pavements subgrade soils. Road Materials and Pavement Design. 19(1). 139–153. 37 indexed citations
13.
Sadrossadat, Ehsan, et al.. (2016). Prediction of the resilient modulus of flexible pavement subgrade soils using adaptive neuro-fuzzy inference systems. Construction and Building Materials. 123. 235–247. 86 indexed citations
14.
Sadrossadat, Ehsan, et al.. (2015). Indirect estimation of the ultimate bearing capacity of shallow foundations resting on rock masses. International Journal of Rock Mechanics and Mining Sciences. 80. 107–117. 32 indexed citations
15.
Sadrossadat, Ehsan, et al.. (2014). Explicit formulation of bearing capacity of shallow foundations on rock masses using artificial neural networks: application and supplementary studies. Environmental Earth Sciences. 73(7). 3417–3431. 47 indexed citations
16.
Alavi, Amir H. & Ehsan Sadrossadat. (2014). New design equations for estimation of ultimate bearing capacity of shallow foundations resting on rock masses. Geoscience Frontiers. 7(1). 91–99. 43 indexed citations
17.
Sadrossadat, Ehsan, et al.. (2014). A NEW DESIGN EQUATION FOR PREDICTION OF ULTIMATE BEARING CAPACITY OF SHALLOW FOUNDATION ON GRANULAR SOILS. Journal of Civil Engineering and Management. 19(Supplement_1). S78–S90. 24 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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