Nima Khodadadi

166 total papers · 5.8k total citations
107 papers, 3.4k citations indexed

About

Nima Khodadadi is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Civil and Structural Engineering. According to data from OpenAlex, Nima Khodadadi has authored 107 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Artificial Intelligence, 36 papers in Computational Theory and Mathematics and 25 papers in Civil and Structural Engineering. Recurrent topics in Nima Khodadadi's work include Metaheuristic Optimization Algorithms Research (44 papers), Advanced Multi-Objective Optimization Algorithms (36 papers) and Evolutionary Algorithms and Applications (21 papers). Nima Khodadadi is often cited by papers focused on Metaheuristic Optimization Algorithms Research (44 papers), Advanced Multi-Objective Optimization Algorithms (36 papers) and Evolutionary Algorithms and Applications (21 papers). Nima Khodadadi collaborates with scholars based in United States, Australia and Egypt. Nima Khodadadi's co-authors include Seyedali Mirjalili, El‐Sayed M. El‐kenawy, Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Abdelaziz A. Abdelhamid, Marwa M. Eid, Farhad Soleimanian Gharehchopogh, Benyamın Abdollahzadeh, Siamak Talatahari, Laith Abualigah and A. Kaveh and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Nima Khodadadi

104 papers receiving 3.3k citations

Hit Papers

Mountain Gazelle Optimize... 2022 2026 2023 2024 2022 2023 2024 2024 2023 50 100 150 200 250
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 benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. Mountain Gazelle Optimizer: A new Nature-inspired Metaheuristic Algorithm for Global Optimization Problems
    2022 299 citations Benyamın Abdollahzadeh, Farhad Soleimanian Gharehchopogh et al. Advances in Engineering Software profile →
  2. Greylag Goose Optimization: Nature-inspired optimization algorithm
    2023 294 citations El‐Sayed M. El‐kenawy, Nima Khodadadi et al. Expert Systems with Applications profile →
  3. Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm
    2024 246 citations Mohammad Hussein Amiri, Mohsen Montazeri et al. Scientific Reports profile →
  4. Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning
    2024 220 citations Benyamın Abdollahzadeh, Nima Khodadadi et al. Cluster Computing profile →
  5. Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications
    2023 156 citations Weiguo Zhao, Liying Wang et al. Expert Systems with Applications profile →
  6. Quadratic Interpolation Optimization (QIO): A new optimization algorithm based on generalized quadratic interpolation and its applications to real-world engineering problems
    2023 104 citations Weiguo Zhao, Liying Wang et al. Computer Methods in Applied Mechanics and Engineering profile →
  7. Fiber-reinforced polymer (FRP) in concrete: A comprehensive survey
    2024 50 citations Nima Khodadadi, Francisco De Caso et al. Construction and Building Materials profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Nima Khodadadi 1.4k 752 521 457 375 107 3.4k
Doddy Prayogo 1.2k 0.8× 859 1.1× 390 0.7× 830 1.8× 297 0.8× 55 2.7k
Mohammad Khishe 1.8k 1.3× 489 0.7× 770 1.5× 343 0.8× 371 1.0× 150 4.1k
Ardeshir Bahreininejad 1.9k 1.4× 1.3k 1.7× 555 1.1× 685 1.5× 629 1.7× 56 4.2k
Gerhard Venter 802 0.6× 825 1.1× 446 0.9× 420 0.9× 441 1.2× 68 3.1k
Sadiq M. Sait 1.4k 1.0× 1.0k 1.4× 389 0.7× 547 1.2× 371 1.0× 61 2.9k
Apu Kumar Saha 1.4k 0.9× 817 1.1× 348 0.7× 152 0.3× 323 0.9× 138 2.8k
Weiguo Zhao 1.9k 1.4× 896 1.2× 1.1k 2.0× 247 0.5× 781 2.1× 115 4.7k
Nantiwat Pholdee 1.6k 1.1× 1.6k 2.1× 390 0.7× 953 2.1× 373 1.0× 94 3.5k
Yu‐Jun Zheng 1.2k 0.8× 422 0.6× 261 0.5× 202 0.4× 261 0.7× 111 3.0k
Dexuan Zou 941 0.7× 508 0.7× 887 1.7× 339 0.7× 339 0.9× 111 2.6k

Countries citing papers authored by Nima Khodadadi

Since Specialization
Citations

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

Fields of papers citing papers by Nima Khodadadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nima Khodadadi

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

All Works

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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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2026