M.Z. Naser

6.7k total citations · 4 hit papers
191 papers, 4.9k citations indexed

About

M.Z. Naser is a scholar working on Civil and Structural Engineering, Building and Construction and Safety, Risk, Reliability and Quality. According to data from OpenAlex, M.Z. Naser has authored 191 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 129 papers in Civil and Structural Engineering, 60 papers in Building and Construction and 39 papers in Safety, Risk, Reliability and Quality. Recurrent topics in M.Z. Naser's work include Fire effects on concrete materials (79 papers), Structural Behavior of Reinforced Concrete (53 papers) and Structural Response to Dynamic Loads (42 papers). M.Z. Naser is often cited by papers focused on Fire effects on concrete materials (79 papers), Structural Behavior of Reinforced Concrete (53 papers) and Structural Response to Dynamic Loads (42 papers). M.Z. Naser collaborates with scholars based in United States, United Arab Emirates and India. M.Z. Naser's co-authors include Venkatesh Kodur, Rami A. Hawileh, Jamal A. Abdalla, Amir H. Alavi, N. Anand, Huu‐Tai Thai, Hadi Salehi, A. Diana Andrushia, Roya Solhmirzaei and Hayder A. Rasheed and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Journal of Cleaner Production.

In The Last Decade

M.Z. Naser

177 papers receiving 4.7k citations

Hit Papers

Fiber-reinforced polymer composites in strengthening rein... 2019 2026 2021 2023 2019 2021 2022 2024 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. Fiber-reinforced polymer composites in strengthening reinforced concrete structures: A critical review
    2019 385 citations M.Z. Naser, Rami A. Hawileh et al. Engineering Structures profile →
  2. Error Metrics and Performance Fitness Indicators for Artificial Intelligence and Machine Learning in Engineering and Sciences
    2021 278 citations M.Z. Naser et al. profile →
  3. Artificial Intelligence, Machine Learning, and Deep Learning in Structural Engineering: A Scientometrics Review of Trends and Best Practices
    2022 166 citations M.Z. Naser et al. profile →
  4. A review on machine learning and deep learning image-based plant disease classification for industrial farming systems
    2024 66 citations A. Diana Andrushia, N. Anand et al. Journal of Industrial Information Integration profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M.Z. Naser United States 41 3.5k 2.1k 607 321 267 191 4.9k
Khalid M. Mosalam United States 41 5.6k 1.6× 2.0k 0.9× 431 0.7× 750 2.3× 184 0.7× 178 6.5k
Cheng Zhou China 30 977 0.3× 735 0.4× 470 0.8× 360 1.1× 56 0.2× 95 3.2k
Sujith Mangalathu India 35 4.5k 1.3× 1.3k 0.6× 320 0.5× 427 1.3× 208 0.8× 106 5.6k
Reginald DesRoches United States 56 10.1k 2.9× 3.0k 1.4× 262 0.4× 532 1.7× 2.4k 8.9× 210 11.6k
Jong Wan Hu South Korea 30 2.4k 0.7× 929 0.4× 104 0.2× 580 1.8× 341 1.3× 272 3.8k
David Infield United Kingdom 45 430 0.1× 843 0.4× 468 0.8× 653 2.0× 216 0.8× 198 8.3k
Michael Havbro Faber Denmark 31 2.3k 0.7× 410 0.2× 540 0.9× 689 2.1× 181 0.7× 254 4.0k
You Dong Hong Kong 35 3.5k 1.0× 853 0.4× 196 0.3× 326 1.0× 245 0.9× 198 4.4k
Hosein Naderpour Iran 31 3.2k 0.9× 1.7k 0.8× 76 0.1× 174 0.5× 91 0.3× 161 3.7k
Yi Zhang China 31 1.4k 0.4× 544 0.3× 290 0.5× 375 1.2× 251 0.9× 277 3.3k

Countries citing papers authored by M.Z. Naser

Since Specialization
Citations

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

Fields of papers citing papers by M.Z. Naser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.Z. Naser. 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 M.Z. Naser. The network helps show where M.Z. Naser may publish in the future.

Co-authorship network of co-authors of M.Z. Naser

This figure shows the co-authorship network connecting the top 25 collaborators of M.Z. Naser. A scholar is included among the top collaborators of M.Z. Naser 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 M.Z. Naser. M.Z. Naser 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.
Naser, M.Z.. (2025). Intuitive tests to validate machine learning models against physics and domain knowledge. SHILAP Revista de lepidopterología. 7. 100057–100057. 3 indexed citations
2.
Andrushia, A. Diana, et al.. (2025). Improved YOLOv5-based multi-crack detection in concrete wall surfaces. SHILAP Revista de lepidopterología. 23. 100247–100247.
3.
Naser, M.Z.. (2025). From failure to fusion: A survey on learning from bad machine learning models. Information Fusion. 120. 103122–103122. 3 indexed citations
4.
Jafari, Abouzar, Amir Ali Shahmansouri, Habib Akbarzadeh Bengar, & M.Z. Naser. (2024). Post-heating flexural behavior of steel fiber reinforced SCC beams strengthened with NSM-CFRP strips: Experimentation and analytical modeling. Construction and Building Materials. 451. 138846–138846. 4 indexed citations
5.
6.
Wiśniewska, Paulina, Elnaz Movahedifar, Krzysztof Formela, et al.. (2024). The chemistry, properties and performance of flame-retardant rubber composites: Collecting, analyzing, categorizing, machine learning modeling, and visualizing. Composites Science and Technology. 250. 110517–110517. 18 indexed citations
7.
Naser, M.Z., et al.. (2024). High‐throughput phenotyping platforms for pulse crop biofortification. Plants People Planet. 7(1). 49–61. 3 indexed citations
8.
9.
Andrushia, A. Diana, et al.. (2024). A review on machine learning and deep learning image-based plant disease classification for industrial farming systems. Journal of Industrial Information Integration. 38. 100572–100572. 66 indexed citations breakdown →
10.
Andrushia, A. Diana, et al.. (2024). A deep learning approach to detect diseases in pomegranate fruits via hybrid optimal attention capsule network. Ecological Informatics. 84. 102859–102859. 5 indexed citations
11.
Hawileh, Rami A., et al.. (2024). Impact of the variability of material constitutive models on the thermal response of reinforced concrete walls. Journal of Structural Fire Engineering. 15(4). 582–602. 2 indexed citations
12.
Naser, M.Z., et al.. (2024). Evacuation preparedness and intellectual disability: Insights from a university fire drill. Journal of Building Engineering. 84. 108578–108578. 11 indexed citations
13.
14.
Naser, M.Z., et al.. (2023). Machine learning and model driven bayesian uncertainty quantification in suspended nonstructural systems. Reliability Engineering & System Safety. 237. 109392–109392. 10 indexed citations
15.
Tarawneh, Ahmad, et al.. (2023). Proposing a one-way shear design model for FRP-RC members: Evaluation and reliability calibration. Engineering Structures. 292. 116527–116527. 3 indexed citations
16.
Post, Christopher J., et al.. (2023). Evaluating Urban Stream Flooding with Machine Learning, LiDAR, and 3D Modeling. Water. 15(14). 2581–2581. 11 indexed citations
17.
Hawileh, Rami A., et al.. (2023). Assessment of critical parameters affecting the behaviour of bearing reinforced concrete walls under fire exposure. Journal of Structural Fire Engineering. 15(3). 362–382. 2 indexed citations
18.
Kanagaraj, Balamurali, N. Anand, A. Diana Andrushia, & M.Z. Naser. (2023). Recent developments of radiation shielding concrete in nuclear and radioactive waste storage facilities – A state of the art review. Construction and Building Materials. 404. 133260–133260. 72 indexed citations
19.
Naser, M.Z., et al.. (2022). Machine learning for wildfire classification: Exploring blackbox, eXplainable, symbolic, and SMOTE methods. SHILAP Revista de lepidopterología. 2(3). 154–165. 17 indexed citations
20.
Kanagaraj, Balamurali, et al.. (2022). Physical characteristics and mechanical properties of a sustainable lightweight geopolymer based self-compacting concrete with expanded clay aggregates. Developments in the Built Environment. 13. 100115–100115. 32 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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