Sayali Kulkarni

4 papers and 173 indexed citations i.

About

Sayali Kulkarni is a scholar working on Artificial Intelligence, Ecological Modeling and Ecology. According to data from OpenAlex, Sayali Kulkarni has authored 4 papers receiving a total of 173 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Ecological Modeling and 1 paper in Ecology. Recurrent topics in Sayali Kulkarni’s work include Species Distribution and Climate Change (2 papers), COVID-19 diagnosis using AI (1 paper) and Artificial Intelligence in Healthcare (1 paper). Sayali Kulkarni is often cited by papers focused on Species Distribution and Climate Change (2 papers), COVID-19 diagnosis using AI (1 paper) and Artificial Intelligence in Healthcare (1 paper). Sayali Kulkarni collaborates with scholars based in United States and United Kingdom. Sayali Kulkarni's co-authors include Alessandro Presta, Jason Baldridge, Daniel Gillick, Eugene Ie, Jorge Ahumada, Tanya Birch, Roland Kays, Margaret F. Kinnaird, Ruth Y. Oliver and Walter Jetz and has published in prestigious journals such as Environmental Conservation, arXiv (Cornell University) and Journal of University of Shanghai for Science and Technology.

In The Last Decade

Co-authorship network of co-authors of Sayali Kulkarni i

Fields of papers citing papers by Sayali Kulkarni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Sayali Kulkarni

Since Specialization
Citations

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