Maya John

5 papers and 29 indexed citations i.

About

Maya John is a scholar working on Modeling and Simulation, Electrical and Electronic Engineering and Sociology and Political Science. According to data from OpenAlex, Maya John has authored 5 papers receiving a total of 29 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Modeling and Simulation, 1 paper in Electrical and Electronic Engineering and 1 paper in Sociology and Political Science. Recurrent topics in Maya John’s work include COVID-19 epidemiological studies (2 papers), Online and Blended Learning (1 paper) and IoT-based Smart Home Systems (1 paper). Maya John is often cited by papers focused on COVID-19 epidemiological studies (2 papers), Online and Blended Learning (1 paper) and IoT-based Smart Home Systems (1 paper). Maya John collaborates with scholars based in Saudi Arabia and India. Maya John's co-authors include Hadil Shaiba and Souham Meshoul and has published in prestigious journals such as Heliyon, Journal of Infection and Public Health and Procedia Computer Science.

In The Last Decade

Co-authorship network of co-authors of Maya John i

Fields of papers citing papers by Maya John

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Maya John

Since Specialization
Citations

This map shows the geographic impact of Maya John'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 Maya John with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya John 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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2025