Bawar Iftikhar

784 total citations · 1 hit paper
22 papers, 613 citations indexed

About

Bawar Iftikhar is a scholar working on Civil and Structural Engineering, Building and Construction and Mechanical Engineering. According to data from OpenAlex, Bawar Iftikhar has authored 22 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Civil and Structural Engineering, 16 papers in Building and Construction and 2 papers in Mechanical Engineering. Recurrent topics in Bawar Iftikhar's work include Innovative concrete reinforcement materials (20 papers), Concrete and Cement Materials Research (12 papers) and Innovations in Concrete and Construction Materials (9 papers). Bawar Iftikhar is often cited by papers focused on Innovative concrete reinforcement materials (20 papers), Concrete and Cement Materials Research (12 papers) and Innovations in Concrete and Construction Materials (9 papers). Bawar Iftikhar collaborates with scholars based in Pakistan, Saudi Arabia and Malaysia. Bawar Iftikhar's co-authors include Muhammad Nasir Amin, Muhammad Faisal Javed, Kaffayatullah Khan, Fahid Aslam, Sophia C. Alih, Mohammadreza Vafaei, Muhammad Faisal Rehman, Muhammad Faisal Javed, M. Ijaz Khan and Rayed Alyousef and has published in prestigious journals such as Journal of Cleaner Production, Scientific Reports and Construction and Building Materials.

In The Last Decade

Bawar Iftikhar

21 papers receiving 602 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.

Prediction model for rice husk ash concrete using AI approach: Boosting and bagging algorithms

2023 93 citations Muhammad Nasir Amin, Bawar Iftikhar et al. Structures profile →

Peers

Bawar Iftikhar

CSE

POLLU

Afnan Nafees Pakistan

Farshad Dabbaghi Iran

Ammar N. Hanoon Iraq

Muhammad Faisal Rehman Pakistan

Aso A. Abdalla Iraq

Baboo Rai India

Manish Kewalramani United Arab Emirates

Hamid Sinaei Malaysia

Amir Hossein Rafiean Iran

Yongcheng Ji China

Afnan Nafees Pakistan

Bawar Iftikhar

502 ×1.0

CSE

262 ×0.8

38 ×1.1

POLLU

44 ×1.4

44 ×1.8

Citations per year, relative to Bawar Iftikhar Bawar Iftikhar (= 1×) peers Afnan Nafees

Countries citing papers authored by Bawar Iftikhar

Since Specialization

Citations

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

Fields of papers citing papers by Bawar Iftikhar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bawar Iftikhar

This figure shows the co-authorship network connecting the top 25 collaborators of Bawar Iftikhar. A scholar is included among the top collaborators of Bawar Iftikhar 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 Bawar Iftikhar. Bawar Iftikhar 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

Amin, Muhammad Nasir, et al.. (2025). Predicting strength in polypropylene fiber reinforced rubberized concrete using symbolic regression AI techniques. Case Studies in Construction Materials. 23. e05024–e05024. 3 indexed citations

Amin, Muhammad Nasir, et al.. (2025). Advanced explainable models for strength evaluation of self-compacting concrete modified with supplementary glass and marble powders. REVIEWS ON ADVANCED MATERIALS SCIENCE. 64(1).

Amin, Muhammad Nasir, et al.. (2025). Foamed geopolymers as low carbon materials for fire-resistant and lightweight applications in construction: A review. REVIEWS ON ADVANCED MATERIALS SCIENCE. 64(1). 1 indexed citations

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2024). Sustainable use of plastic waste in plastic sand paver blocks: An experimental and modelling-based study. Structures. 62. 106285–106285. 6 indexed citations

Amin, Muhammad Nasir, et al.. (2024). Investigating the effectiveness of carbon nanotubes for the compressive strength of concrete using AI-aided tools. Case Studies in Construction Materials. 20. e03083–e03083. 13 indexed citations

Iftikhar, Bawar, Ayaz Ahmad, Yakubu Aminu Dodo, et al.. (2023). Strength evaluation of eco-friendly waste-derived self-compacting concrete via interpretable genetic-based machine learning models. Materials Today Communications. 37. 107356–107356. 13 indexed citations

Zou, Baoping, Yanbing Wang, Muhammad Nasir Amin, et al.. (2023). Artificial intelligence-based optimized models for predicting the slump and compressive strength of sustainable alkali-derived concrete. Construction and Building Materials. 409. 134092–134092. 22 indexed citations

Chen, Zhiqiang, Muhammad Nasir Amin, Bawar Iftikhar, et al.. (2023). Predictive modelling for the acid resistance of cement-based composites modified with eggshell and glass waste for sustainable and resilient building materials. Journal of Building Engineering. 76. 107325–107325. 29 indexed citations

Jiang, Xi, et al.. (2023). An overview on spalling behavior, mechanism, residual strength and microstructure of fiber reinforced concrete under high temperatures. Frontiers in Materials. 10. 8 indexed citations

10.

Amin, Muhammad Nasir, et al.. (2023). Prediction model for rice husk ash concrete using AI approach: Boosting and bagging algorithms. Structures. 50. 745–757. 93 indexed citations breakdown →

11.

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2023). Experimental study on the eco-friendly plastic-sand paver blocks by utilising plastic waste and basalt fibers. Heliyon. 9(6). e17107–e17107. 30 indexed citations

12.

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2023). Predicting compressive strength of eco-friendly plastic sand paver blocks using gene expression and artificial intelligence programming. Scientific Reports. 13(1). 12149–12149. 38 indexed citations

13.

Althoey, Fadi, et al.. (2023). An overview of recent advancements in fibre-reinforced 3D printing concrete. Frontiers in Materials. 10. 3 indexed citations

14.

Li, Yingjie, Muhammad Nasir Amin, Bawar Iftikhar, et al.. (2023). Fresh state and strength performance evaluation of slag-based alkali-activated concrete using soft-computing methods. Materials Today Communications. 38. 107822–107822. 7 indexed citations

15.

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2023). A scientometric analysis approach on the plastic sand. Heliyon. 9(3). e14457–e14457. 15 indexed citations

16.

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2023). A machine learning-based genetic programming approach for the sustainable production of plastic sand paver blocks. Journal of Materials Research and Technology. 25. 5705–5719. 22 indexed citations

17.

Qureshi, Hisham Jahangir, Mana Alyami, Rab Nawaz, et al.. (2023). Prediction of compressive strength of two-stage (preplaced aggregate) concrete using gene expression programming and random forest. Case Studies in Construction Materials. 19. e02581–e02581. 20 indexed citations

18.

Zhang, Yin, et al.. (2023). Towards modern sustainable construction materials: a bibliographic analysis of engineered geopolymer composites. Frontiers in Materials. 10. 14 indexed citations

19.

Iftikhar, Bawar, Sophia C. Alih, Mohammadreza Vafaei, et al.. (2022). Predictive modeling of compressive strength of sustainable rice husk ash concrete: Ensemble learner optimization and comparison. Journal of Cleaner Production. 348. 131285–131285. 118 indexed citations

20.

Javed, Muhammad Faisal, Muhammad Nasir Amin, Muhammad Izhar Shah, et al.. (2020). Applications of Gene Expression Programming and Regression Techniques for Estimating Compressive Strength of Bagasse Ash based Concrete. Crystals. 10(9). 737–737. 143 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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