Fahid Aslam

8.2k total citations · 8 hit papers
116 papers, 6.2k citations indexed

About

Fahid Aslam is a scholar working on Civil and Structural Engineering, Building and Construction and Materials Chemistry. According to data from OpenAlex, Fahid Aslam has authored 116 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Civil and Structural Engineering, 73 papers in Building and Construction and 8 papers in Materials Chemistry. Recurrent topics in Fahid Aslam's work include Innovative concrete reinforcement materials (82 papers), Concrete and Cement Materials Research (65 papers) and Recycled Aggregate Concrete Performance (36 papers). Fahid Aslam is often cited by papers focused on Innovative concrete reinforcement materials (82 papers), Concrete and Cement Materials Research (65 papers) and Recycled Aggregate Concrete Performance (36 papers). Fahid Aslam collaborates with scholars based in Saudi Arabia, Pakistan and China. Fahid Aslam's co-authors include Furqan Farooq, Rayed Alyousef, Ayaz Ahmad, Muhammad Faisal Javed, Waqas Ahmad, Panuwat Joyklad, Hisham Alabduljabbar, Krzysztof Adam Ostrowski, Arslan Akbar and Muhammad Nasir Amin and has published in prestigious journals such as Journal of Cleaner Production, Scientific Reports and Construction and Building Materials.

In The Last Decade

Fahid Aslam

112 papers receiving 6.0k citations

Hit Papers

Predictive modeling for sustainable high-performance conc... 2020 2026 2022 2024 2021 2021 2021 2021 2020 100 200 300
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. Predictive modeling for sustainable high-performance concrete from industrial wastes: A comparison and optimization of models using ensemble learners
    2021 335 citations Furqan Farooq, Arslan Akbar et al. profile →
  2. Predicting the compressive strength of concrete with fly ash admixture using machine learning algorithms
    2021 284 citations Ayaz Ahmad, Furqan Farooq et al. Construction and Building Materials profile →
  3. Compressive strength prediction of fly ash-based geopolymer concrete via advanced machine learning techniques
    2021 241 citations Ayaz Ahmad, Waqas Ahmad et al. Case Studies in Construction Materials profile →
  4. Geopolymer concrete as sustainable material: A state of the art review
    2021 237 citations Furqan Farooq, Muhammad Faisal Javed et al. Construction and Building Materials profile →
  5. A Comparative Study of Random Forest and Genetic Engineering Programming for the Prediction of Compressive Strength of High Strength Concrete (HSC)
    2020 216 citations Furqan Farooq, Muhammad Nasir Amin et al. profile →
  6. Prediction of Compressive Strength of Fly Ash Based Concrete Using Individual and Ensemble Algorithm
    2021 203 citations Ayaz Ahmad, Furqan Farooq et al. Materials profile →
  7. Compressive Strength of Fly‐Ash‐Based Geopolymer Concrete by Gene Expression Programming and Random Forest
    2021 175 citations Mohsin Ali Khan, Furqan Farooq et al. profile →
  8. Compressive Strength Prediction via Gene Expression Programming (GEP) and Artificial Neural Network (ANN) for Concrete Containing RCA
    2021 160 citations Ayaz Ahmad, Furqan Farooq et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fahid Aslam Saudi Arabia 46 5.1k 3.3k 482 418 288 116 6.2k
Hisham Alabduljabbar Saudi Arabia 38 4.3k 0.8× 3.2k 1.0× 594 1.2× 350 0.8× 341 1.2× 128 5.5k
Muhammad Nasir Amin Saudi Arabia 38 3.9k 0.8× 2.2k 0.7× 470 1.0× 314 0.8× 210 0.7× 252 5.0k
Ahmed Farouk Deifalla Egypt 41 3.7k 0.7× 2.9k 0.9× 447 0.9× 721 1.7× 236 0.8× 243 5.4k
Shaker Qaidi Iraq 42 4.5k 0.9× 2.7k 0.8× 853 1.8× 300 0.7× 172 0.6× 63 5.3k
Kaffayatullah Khan Saudi Arabia 38 3.4k 0.7× 2.1k 0.6× 409 0.8× 239 0.6× 179 0.6× 152 4.3k
Rayed Alyousef Saudi Arabia 45 6.8k 1.3× 5.0k 1.5× 1.0k 2.1× 550 1.3× 419 1.5× 152 8.4k
İlker Bekir Topçu Türkiye 44 6.4k 1.3× 4.6k 1.4× 766 1.6× 336 0.8× 284 1.0× 136 7.3k
G. Murali India 39 3.9k 0.8× 2.7k 0.8× 688 1.4× 286 0.7× 195 0.7× 167 4.7k
Bashar S. Mohammed Malaysia 42 4.0k 0.8× 3.0k 0.9× 610 1.3× 201 0.5× 221 0.8× 169 4.8k
Aliakbar Gholampour Australia 40 3.8k 0.7× 3.1k 1.0× 777 1.6× 379 0.9× 144 0.5× 114 5.4k

Countries citing papers authored by Fahid Aslam

Since Specialization
Citations

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

Fields of papers citing papers by Fahid Aslam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fahid Aslam

This figure shows the co-authorship network connecting the top 25 collaborators of Fahid Aslam. A scholar is included among the top collaborators of Fahid Aslam 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 Fahid Aslam. Fahid Aslam 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.
Saleem, M. A. M., et al.. (2024). Statistical insight into the quality of reinforcing steel bars used in construction projects. Case Studies in Construction Materials. 21. e03698–e03698.
2.
Javed, Muhammad Faisal, et al.. (2024). Data-driven evolutionary programming for evaluating the mechanical properties of concrete containing plastic waste. Case Studies in Construction Materials. 21. e03763–e03763. 6 indexed citations
3.
Rizwan, Muhammad, et al.. (2024). Optimizing hybrid fiber content for enhanced thermo-mechanical performance of high-strength concrete. Materials Today Communications. 39. 109293–109293. 4 indexed citations
4.
Aslam, Fahid, Rayed Alyousef, Hamad Hassan Awan, & Muhammad Faisal Javed. (2023). Forecasting the self-healing capacity of engineered cementitious composites using bagging regressor and stacking regressor. Structures. 54. 1717–1728. 16 indexed citations
5.
Khan, Mohsin Ali, et al.. (2023). Metaheuristic artificial intelligence (AI): Mechanical properties of electronic waste concrete. Construction and Building Materials. 394. 132012–132012. 4 indexed citations
6.
7.
Abbass, Wasim, et al.. (2022). Manufacturing of Sustainable Untreated Coal Ash Masonry Units for Structural Applications. Materials. 15(11). 4003–4003. 16 indexed citations
8.
Nazir, Kashif, Muhammad Ishtiaq, Muhammad Faisal Javed, et al.. (2022). Concrete by Preplaced Aggregate Method Using Silica Fume and Polypropylene Fibres. Materials. 15(6). 1997–1997. 9 indexed citations
9.
Ahmad, Jawad, Osama Zaid, Fahid Aslam, et al.. (2021). Mechanical properties and durability assessment of nylon fiber reinforced self-compacting concrete. Journal of Engineered Fibers and Fabrics. 16. 20 indexed citations
10.
Farooq, Furqan, Sławomir Czarnecki, Paweł Niewiadomski, et al.. (2021). A Comparative Study for the Prediction of the Compressive Strength of Self-Compacting Concrete Modified with Fly Ash. Materials. 14(17). 4934–4934. 104 indexed citations
11.
Khan, Mohsin Ali, Furqan Farooq, Muhammad Faisal Javed, et al.. (2021). Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches. Materials. 15(1). 58–58. 72 indexed citations
12.
Xu, Yue, Waqas Ahmad, Ayaz Ahmad, et al.. (2021). Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques. Materials. 14(22). 7034–7034. 67 indexed citations
13.
Shah, Muhammad Izhar, Muhammad Nasir Amin, Kaffayatullah Khan, et al.. (2021). Performance Evaluation of Soft Computing for Modeling the Strength Properties of Waste Substitute Green Concrete. Sustainability. 13(5). 2867–2867. 37 indexed citations
14.
Zhang, Bin, Waqas Ahmad, Ayaz Ahmad, Fahid Aslam, & Panuwat Joyklad. (2021). A scientometric analysis approach to analyze the present research on recycled aggregate concrete. Journal of Building Engineering. 46. 103679–103679. 57 indexed citations
15.
Khan, Niaz Bahadur, Sardar Kashif Ur Rehman, Muhammad Faisal Javed, et al.. (2021). Prediction of Compressive Strength of Rice Husk Ash Concrete through Different Machine Learning Processes. Crystals. 11(4). 352–352. 51 indexed citations
16.
Rehman, Sardar Kashif Ur, Wesam Salah Alaloul, Kashif Nazir, et al.. (2021). Life Cycle Impact Assessment of Recycled Aggregate Concrete, Geopolymer Concrete, and Recycled Aggregate-Based Geopolymer Concrete. Sustainability. 13(24). 13515–13515. 70 indexed citations
17.
Alyousef, Rayed, et al.. (2020). Flexural strength improvement in bamboo reinforced concrete beams subjected to pure bending. Journal of Building Engineering. 31. 101289–101289. 41 indexed citations
18.
Akbar, Arslan, Furqan Farooq, Muhammad Shafique, et al.. (2020). Sugarcane bagasse ash-based engineered geopolymer mortar incorporating propylene fibers. Journal of Building Engineering. 33. 101492–101492. 110 indexed citations
19.
Ahmad, Waqas, Syed Hassan Farooq, Muhammad Usman, et al.. (2020). Effect of Coconut Fiber Length and Content on Properties of High Strength Concrete. Materials. 13(5). 1075–1075. 159 indexed citations
20.
Yaqub, M., Sardar Kashif Ur Rehman, Muhammad Abid, et al.. (2019). Performance of Foundry Sand Concrete under Ambient and Elevated Temperatures. Materials. 12(16). 2645–2645. 43 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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