Rupesh Kumar Tipu

721 total citations
47 papers, 431 citations indexed

About

Rupesh Kumar Tipu is a scholar working on Civil and Structural Engineering, Building and Construction and Artificial Intelligence. According to data from OpenAlex, Rupesh Kumar Tipu has authored 47 papers receiving a total of 431 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Civil and Structural Engineering, 19 papers in Building and Construction and 4 papers in Artificial Intelligence. Recurrent topics in Rupesh Kumar Tipu's work include Innovative concrete reinforcement materials (24 papers), Infrastructure Maintenance and Monitoring (20 papers) and Concrete and Cement Materials Research (13 papers). Rupesh Kumar Tipu is often cited by papers focused on Innovative concrete reinforcement materials (24 papers), Infrastructure Maintenance and Monitoring (20 papers) and Concrete and Cement Materials Research (13 papers). Rupesh Kumar Tipu collaborates with scholars based in India, Saudi Arabia and United Kingdom. Rupesh Kumar Tipu's co-authors include Kartik S. Pandya, V. R. Panchal, Rishabh Arora, Kaushal Kumar, Mahesh Patel, Rajwinder Singh, Haytham F. Isleem, Satvik Vats, Mohammad Khishe and Saad A. Yehia and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Rupesh Kumar Tipu

35 papers receiving 414 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rupesh Kumar Tipu India 15 319 190 20 18 14 47 431
Palika Chopra India 5 312 1.0× 144 0.8× 14 0.7× 39 2.2× 14 1.0× 7 358
Amirreza Kandiri Iran 7 327 1.0× 218 1.1× 16 0.8× 31 1.7× 19 1.4× 11 413
Behnam Vakhshouri Australia 8 323 1.0× 182 1.0× 13 0.7× 9 0.5× 9 0.6× 24 362
Md. Nafiur Rahman United States 10 220 0.7× 122 0.6× 16 0.8× 12 0.7× 11 0.8× 29 329
Bakhta Boukhatem Algeria 13 480 1.5× 177 0.9× 22 1.1× 36 2.0× 22 1.6× 19 534
Hisham Jahangir Qureshi Saudi Arabia 13 255 0.8× 144 0.8× 14 0.7× 38 2.1× 11 0.8× 28 321
Komeil Rahmati Iran 8 342 1.1× 206 1.1× 12 0.6× 29 1.6× 28 2.0× 9 424
Mohammad Haji Iran 8 384 1.2× 264 1.4× 7 0.3× 20 1.1× 12 0.9× 12 420
Ahmad Tarawneh Jordan 14 444 1.4× 328 1.7× 11 0.6× 34 1.9× 20 1.4× 56 500
Bochao Sun China 11 272 0.9× 154 0.8× 6 0.3× 22 1.2× 15 1.1× 30 359

Countries citing papers authored by Rupesh Kumar Tipu

Since Specialization
Citations

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

Fields of papers citing papers by Rupesh Kumar Tipu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rupesh Kumar Tipu. 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 Rupesh Kumar Tipu. The network helps show where Rupesh Kumar Tipu may publish in the future.

Co-authorship network of co-authors of Rupesh Kumar Tipu

This figure shows the co-authorship network connecting the top 25 collaborators of Rupesh Kumar Tipu. A scholar is included among the top collaborators of Rupesh Kumar Tipu 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 Rupesh Kumar Tipu. Rupesh Kumar Tipu 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.
Isleem, Haytham F., et al.. (2025). An ANN-based approach for estimating load capacity and strain in FRP confined concrete columns. Egyptian Informatics Journal. 31. 100738–100738.
2.
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Tipu, Rupesh Kumar, et al.. (2025). Advancing Water Quality Management: An Integrated Approach Using Ensemble Machine Learning and Real-Time Interactive Visualization. IEEE Access. 13. 92406–92428. 1 indexed citations
4.
Tipu, Rupesh Kumar, et al.. (2025). Physics-informed neural networks for predicting sediment transport in pressurized pipe flows. Environmental Earth Sciences. 84(11).
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Tipu, Rupesh Kumar, et al.. (2025). Predicting compressive and tensile strength of concrete with different sand types using machine learning. Ain Shams Engineering Journal. 16(8). 103474–103474.
7.
Tipu, Rupesh Kumar, et al.. (2025). Integrated deep learning and Bayesian optimization approach for enhanced prediction of high-performance concrete strength. Asian Journal of Civil Engineering. 26(6). 2371–2390. 2 indexed citations
8.
Tipu, Rupesh Kumar, et al.. (2025). Ensemble machine learning models for predicting concrete compressive strength incorporating various sand types. Multiscale and Multidisciplinary Modeling Experiments and Design. 8(4). 3 indexed citations
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Paruthi, Sagar, et al.. (2025). Stacked Ensemble Intelligence for Predicting Compressive Strength of CDW-Incorporated Sustainable Concrete. Iranian Journal of Science and Technology Transactions of Civil Engineering.
11.
Isleem, Haytham F., et al.. (2024). Numerical and machine learning models for concentrically and eccentrically loaded CFST columns confined with FRP wraps. Structural Concrete. 18 indexed citations
12.
Tipu, Rupesh Kumar, Rishabh Arora, & Kaushal Kumar. (2023). Machine learning-based prediction of concrete strength properties with coconut shell as partial aggregate replacement: A sustainable approach in construction engineering. Asian Journal of Civil Engineering. 25(3). 2979–2992. 20 indexed citations
13.
Tipu, Rupesh Kumar, et al.. (2023). Predictive modelling of surface chloride concentration in marine concrete structures: a comparative analysis of machine learning approaches. Asian Journal of Civil Engineering. 25(2). 1443–1465. 16 indexed citations
14.
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Tipu, Rupesh Kumar, et al.. (2023). Shear capacity prediction for FRCM-strengthened RC beams using Hybrid ReLU-Activated BPNN model. Structures. 58. 105432–105432. 20 indexed citations
16.
Tipu, Rupesh Kumar, et al.. (2023). Enhancing prediction accuracy of workability and compressive strength of high-performance concrete through extended dataset and improved machine learning models. Asian Journal of Civil Engineering. 25(1). 197–218. 21 indexed citations
17.
Arora, Rishabh, et al.. (2023). Parametric investigation of coconut shells as partial replacement of coarse aggregates in sustainable concrete. SHILAP Revista de lepidopterología. 430. 1180–1180. 2 indexed citations
18.
Tipu, Rupesh Kumar, V. R. Panchal, & Kartik S. Pandya. (2023). Enhancing chloride concentration prediction in marine concrete using conjugate gradient-optimized backpropagation neural network. Asian Journal of Civil Engineering. 25(1). 637–656. 21 indexed citations
19.
Tipu, Rupesh Kumar, et al.. (2023). ANN-Based Scalable Video Encoding Method for Crime Surveillance-Intelligence of Things Applications. 11. 1–7. 3 indexed citations
20.
Tipu, Rupesh Kumar, V. R. Panchal, & Kartik S. Pandya. (2022). Multi-objective optimized high-strength concrete mix design using a hybrid machine learning and metaheuristic algorithm. Asian Journal of Civil Engineering. 24(3). 849–867. 23 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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