Kazem Meidani

About

Kazem Meidani is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Statistical and Nonlinear Physics. According to data from OpenAlex, Kazem Meidani has authored 10 papers receiving a total of 300 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 3 papers in Statistical and Nonlinear Physics. Recurrent topics in Kazem Meidani’s work include Metaheuristic Optimization Algorithms Research (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Model Reduction and Neural Networks (3 papers). Kazem Meidani is often cited by papers focused on Metaheuristic Optimization Algorithms Research (4 papers), Advanced Multi-Objective Optimization Algorithms (4 papers) and Model Reduction and Neural Networks (3 papers). Kazem Meidani collaborates with scholars based in United States, Australia and South Korea. Kazem Meidani's co-authors include Amir Barati Farimani, Seyedali Mirjalili, Zhonglin Cao, Chun-Yu Yeh, William Lee, Zijie Li and Prakarsh Yadav and has published in prestigious journals such as The Journal of Chemical Physics, Computer Methods in Applied Mechanics and Engineering and Expert Systems with Applications.

In The Last Decade

Co-authorship network of co-authors of Kazem Meidani i

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Fields of papers citing papers by Kazem Meidani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Kazem Meidani

Since Specialization

Citations

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

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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