Kin Gwn Lore

16 papers and 1.2k indexed citations i.

About

Kin Gwn Lore is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics and Aerospace Engineering. According to data from OpenAlex, Kin Gwn Lore has authored 16 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 6 papers in Computational Mechanics and 4 papers in Aerospace Engineering. Recurrent topics in Kin Gwn Lore’s work include Combustion and flame dynamics (4 papers), Aerodynamics and Acoustics in Jet Flows (3 papers) and Advanced Combustion Engine Technologies (3 papers). Kin Gwn Lore is often cited by papers focused on Combustion and flame dynamics (4 papers), Aerodynamics and Acoustics in Jet Flows (3 papers) and Advanced Combustion Engine Technologies (3 papers). Kin Gwn Lore collaborates with scholars based in United States, China and India. Kin Gwn Lore's co-authors include Soumik Sarkar, Adedotun Akintayo, Daniel Stoecklein, Baskar Ganapathysubramanian, Soumalya Sarkar, Michael Giering, Edgar A. Bernal, Kishore Reddy, K. Krishna Reddy and Chao Liu and has published in prestigious journals such as Scientific Reports, Pattern Recognition and Neural Networks.

In The Last Decade

Co-authorship network of co-authors of Kin Gwn Lore i

Fields of papers citing papers by Kin Gwn Lore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kin Gwn Lore. 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 Kin Gwn Lore. The network helps show where Kin Gwn Lore may publish in the future.

Countries citing papers authored by Kin Gwn Lore

Since Specialization
Citations

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