Milan Parmar

About

Milan Parmar is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Milan Parmar has authored 12 papers receiving a total of 306 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Statistical and Nonlinear Physics and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Milan Parmar’s work include Advanced Clustering Algorithms Research (7 papers), Complex Network Analysis Techniques (5 papers) and Anomaly Detection Techniques and Applications (3 papers). Milan Parmar is often cited by papers focused on Advanced Clustering Algorithms Research (7 papers), Complex Network Analysis Techniques (5 papers) and Anomaly Detection Techniques and Applications (3 papers). Milan Parmar collaborates with scholars based in China, United States and Singapore. Milan Parmar's co-authors include Xuming Han, Jianhua Jiang, Limin Wang, Muhammet Deveci, Yufei Zhang, You Zhou, Chunyan Miao, Yunjing Chen, Ah‐Hwee Tan and Qin Lu and has published in prestigious journals such as IEEE Access, Neurocomputing and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Co-authorship network of co-authors of Milan Parmar i

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Fields of papers citing papers by Milan Parmar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Milan Parmar

Since Specialization

Citations

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