Rushil Anirudh

164 total papers · 1.2k total citations
52 papers, 485 citations indexed

About

Rushil Anirudh is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Nuclear and High Energy Physics. According to data from OpenAlex, Rushil Anirudh has authored 52 papers receiving a total of 485 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 8 papers in Nuclear and High Energy Physics. Recurrent topics in Rushil Anirudh's work include Human Pose and Action Recognition (9 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Laser-Plasma Interactions and Diagnostics (8 papers). Rushil Anirudh is often cited by papers focused on Human Pose and Action Recognition (9 papers), Domain Adaptation and Few-Shot Learning (8 papers) and Laser-Plasma Interactions and Diagnostics (8 papers). Rushil Anirudh collaborates with scholars based in United States and India. Rushil Anirudh's co-authors include Jayaraman J. Thiagarajan, Pavan Turaga, Peer‐Timo Bremer, Jingyong Su, Anuj Srivastava, Hyojin Kim, B. K. Spears, Bhavya Kailkhura, Abhinav Bhatelé and Bogdan Kustowski and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Access and International Journal of Computer Vision.

In The Last Decade

Rushil Anirudh

47 papers receiving 479 citations

Author Peers

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

Author						Papers	Cites
Rushil Anirudh	165	148	115	85	60	52	485
Nikolay Nagornov	137 0.8×	154 1.0×	58 0.5×	45 0.5×	35 0.6×	29	533
María Rízzí	77 0.5×	123 0.8×	51 0.4×	94 1.1×	33 0.6×	69	474
Giovanni Danese	105 0.6×	55 0.4×	68 0.6×	121 1.4×	38 0.6×	66	458
Rahul Krishnan	56 0.3×	125 0.8×	19 0.2×	136 1.6×	32 0.5×	75	513
Yang Bai	249 1.5×	219 1.5×	30 0.3×	38 0.4×	40 0.7×	41	543
Mark Christiaens	67 0.4×	42 0.3×	148 1.3×	88 1.0×	123 2.0×	29	409
Yu‐Hsiang Tsai	46 0.3×	116 0.8×	103 0.9×	29 0.3×	59 1.0×	40	420
Feng Chen	243 1.5×	110 0.7×	125 1.1×	84 1.0×	81 1.4×	48	482
Serge Miguet	261 1.6×	59 0.4×	152 1.3×	93 1.1×	59 1.0×	39	449
P.J.G. Lisboa	180 1.1×	216 1.5×	33 0.3×	20 0.2×	14 0.2×	35	531

Countries citing papers authored by Rushil Anirudh

Since Specialization

Citations

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

Fields of papers citing papers by Rushil Anirudh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rushil Anirudh

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