Machine Intelligence Research Labs

About

In recent decades, authors affiliated with Machine Intelligence Research Labs have published 409 papers, which have received a total of 11.4k indexed citations. Scholars at this organization have produced 161 papers in Artificial Intelligence, 73 papers in Computer Vision and Pattern Recognition and 49 papers in Computational Theory and Mathematics on the topics of Metaheuristic Optimization Algorithms Research (71 papers), Evolutionary Algorithms and Applications (41 papers) and Advanced Multi-Objective Optimization Algorithms (36 papers). Their work is cited by papers focused on Artificial Intelligence (4.1k citations), Computer Networks and Communications (1.8k citations) and Computer Vision and Pattern Recognition (1.8k citations). Authors at Machine Intelligence Research Labs collaborate with scholars in United States, India and Czechia and have published in prestigious journals including Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Journal of Cleaner Production. Some of Machine Intelligence Research Labs's most productive authors include Ajith Abraham, Rutuparna Panda, Fariba Goodarzian, Václav Snåšel, Millie Pant, Peiman Ghasemi, Sanjay Agrawal, Varun Ojha, Pranab K. Muhuri and Amit K. Shukla.

In The Last Decade

Machine Intelligence Research Labs

345 papers receiving 10.6k citations

Fields of papers published by authors at Machine Intelligence Research Labs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Machine Intelligence Research Labs at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Machine Intelligence Research Labs at the time of their publication.

Countries citing scholars working at Machine Intelligence Research Labs

Since Specialization
Citations

This map shows the geographic impact of research produced by authors working at Machine Intelligence Research Labs. 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 papers produced at Machine Intelligence Research Labs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Machine Intelligence Research Labs 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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2026