Rajat Raina

16 total papers · 5.6k total citations
11 papers, 2.0k citations indexed

About

Rajat Raina is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Rajat Raina has authored 11 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Rajat Raina's work include Machine Learning and Algorithms (4 papers), Machine Learning and Data Classification (3 papers) and Semantic Web and Ontologies (2 papers). Rajat Raina is often cited by papers focused on Machine Learning and Algorithms (4 papers), Machine Learning and Data Classification (3 papers) and Semantic Web and Ontologies (2 papers). Rajat Raina collaborates with scholars based in United States and France. Rajat Raina's co-authors include Andrew Y. Ng, Honglak Lee, Alexis Battle, Anand Madhavan, Daphne Koller, Andrew McCallum, Roger Grosse, Christopher D. Manning, Alex Teichman and Ding Zhou and has published in prestigious journals such as Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)), International Joint Conference on Artificial Intelligence and National Conference on Artificial Intelligence.

In The Last Decade

Rajat Raina

10 papers receiving 1.9k citations

Hit Papers

Self-taught learning 2007 2026 2013 2019 2007 2009 250 500 750 1000

Author Peers

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

Author Last Decade Papers Cites
Rajat Raina 1.2k 827 234 172 148 11 2.0k
SingerYoram 1.2k 1.0× 644 0.8× 182 0.8× 167 1.0× 228 1.5× 8 1.9k
Yuqiang Guan 1.1k 0.9× 805 1.0× 198 0.8× 110 0.6× 177 1.2× 9 1.8k
Bernd Fritzke 1.6k 1.3× 1.0k 1.2× 303 1.3× 113 0.7× 79 0.5× 14 2.4k
Antonia Creswell 971 0.8× 1.1k 1.4× 239 1.0× 83 0.5× 111 0.8× 6 3.0k
Filip Mulier 905 0.7× 390 0.5× 190 0.8× 83 0.5× 88 0.6× 10 1.9k
Pascal Lamblin 830 0.7× 739 0.9× 282 1.2× 65 0.4× 75 0.5× 9 1.9k
Dennis DeCoste 1.0k 0.8× 920 1.1× 157 0.7× 131 0.8× 227 1.5× 39 2.1k
Afshin Rostamizadeh 1.5k 1.2× 799 1.0× 144 0.6× 172 1.0× 132 0.9× 34 2.6k
Y.P. Chien 1.2k 1.0× 1.1k 1.4× 374 1.6× 99 0.6× 128 0.9× 30 2.8k
宏治 津田 1.0k 0.9× 860 1.0× 163 0.7× 114 0.7× 169 1.1× 2 2.0k

Countries citing papers authored by Rajat Raina

Since Specialization
Citations

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

Fields of papers citing papers by Rajat Raina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rajat Raina

This figure shows the co-authorship network connecting the top 25 collaborators of Rajat Raina. A scholar is included among the top collaborators of Rajat Raina 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 Rajat Raina. Rajat Raina 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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