Sheetal Girase

23 total papers · 587 total citations
14 papers, 295 citations indexed

About

Sheetal Girase is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sheetal Girase has authored 14 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Information Systems, 6 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sheetal Girase's work include Recommender Systems and Techniques (6 papers), Sentiment Analysis and Opinion Mining (3 papers) and Advanced Bandit Algorithms Research (2 papers). Sheetal Girase is often cited by papers focused on Recommender Systems and Techniques (6 papers), Sentiment Analysis and Opinion Mining (3 papers) and Advanced Bandit Algorithms Research (2 papers). Sheetal Girase collaborates with scholars based in India. Sheetal Girase's co-authors include Debajyoti Mukhopadhyay and Ranjana Yadav and has published in prestigious journals such as Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation, Procedia Computer Science and 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

In The Last Decade

Sheetal Girase

13 papers receiving 271 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Sheetal Girase	229	119	89	36	29	14	295
Abinash Pujahari	190 0.8×	118 1.0×	71 0.8×	47 1.3×	29 1.0×	13	332
Aghiles Salah	206 0.9×	178 1.5×	107 1.2×	41 1.1×	21 0.7×	14	301
Inay Ha	230 1.0×	81 0.7×	90 1.0×	23 0.6×	41 1.4×	15	298
Jiangzhou Deng	242 1.1×	120 1.0×	109 1.2×	42 1.2×	45 1.6×	18	323
Yan‐Shuo Chang	179 0.8×	127 1.1×	97 1.1×	21 0.6×	43 1.5×	14	278
Daniel Valcarce	193 0.8×	119 1.0×	51 0.6×	56 1.6×	20 0.7×	20	246
Lei Zhang	171 0.7×	138 1.2×	90 1.0×	22 0.6×	39 1.3×	17	328
Dina Nawara	181 0.8×	141 1.2×	41 0.5×	31 0.9×	67 2.3×	13	322
Diane Hu	181 0.8×	163 1.4×	62 0.7×	57 1.6×	19 0.7×	16	285
Jorge Castro	211 0.9×	104 0.9×	54 0.6×	67 1.9×	30 1.0×	11	275

Countries citing papers authored by Sheetal Girase

Since Specialization

Citations

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

Fields of papers citing papers by Sheetal Girase

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheetal Girase

This figure shows the co-authorship network connecting the top 25 collaborators of Sheetal Girase. A scholar is included among the top collaborators of Sheetal Girase based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sheetal Girase. Sheetal Girase is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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