Nikhil V. Navkar

81 total papers · 703 total citations
52 papers, 469 citations indexed

About

Nikhil V. Navkar is a scholar working on Surgery, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Nikhil V. Navkar has authored 52 papers receiving a total of 469 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Surgery, 30 papers in Computer Vision and Pattern Recognition and 25 papers in Biomedical Engineering. Recurrent topics in Nikhil V. Navkar's work include Surgical Simulation and Training (28 papers), Augmented Reality Applications (23 papers) and Soft Robotics and Applications (17 papers). Nikhil V. Navkar is often cited by papers focused on Surgical Simulation and Training (28 papers), Augmented Reality Applications (23 papers) and Soft Robotics and Applications (17 papers). Nikhil V. Navkar collaborates with scholars based in Qatar, United States and Italy. Nikhil V. Navkar's co-authors include Nikolaos V. Tsekos, Zhigang Deng, Abdulla Al‐Ansari, Dipan J. Shah, Julien Abinahed, Shidin Balakrishnan, Panagiotis Tsiamyrtzis, Aiman Erbad, Elias Yaacoub and Eftychios G. Christoforou and has published in prestigious journals such as IEEE Transactions on Medical Imaging, IEEE Transactions on Biomedical Engineering and Journal of Medical Internet Research.

In The Last Decade

Nikhil V. Navkar

49 papers receiving 461 citations

Author Peers

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

Author						Papers	Cites
Nikhil V. Navkar	312	256	239	45	38	52	469
Andrea Mariani	227 0.7×	310 1.2×	126 0.5×	17 0.4×	24 0.6×	29	531
Tansel Halic	210 0.7×	103 0.4×	189 0.8×	17 0.4×	31 0.8×	59	511
Woo Jin Ahn	273 0.9×	191 0.7×	151 0.6×	23 0.5×	41 1.1×	58	439
Weixin Si	90 0.3×	139 0.5×	191 0.8×	81 1.8×	38 1.0×	66	446
Mahdi Azizian	242 0.8×	299 1.2×	167 0.7×	34 0.8×	38 1.0×	25	485
Hamed Saeidi	206 0.7×	222 0.9×	67 0.3×	44 1.0×	36 0.9×	31	519
Paul M. Novotny	209 0.7×	297 1.2×	137 0.6×	72 1.6×	32 0.8×	23	549
Rahul Agarwal	177 0.6×	150 0.6×	138 0.6×	17 0.4×	49 1.3×	22	458
Diana C. W. Friedman	255 0.8×	245 1.0×	119 0.5×	9 0.2×	28 0.7×	17	470
Jérôme Schmid	213 0.7×	167 0.7×	114 0.5×	60 1.3×	14 0.4×	30	427

Countries citing papers authored by Nikhil V. Navkar

Since Specialization

Citations

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

Fields of papers citing papers by Nikhil V. Navkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nikhil V. Navkar. 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 Nikhil V. Navkar. The network helps show where Nikhil V. Navkar may publish in the future.

Co-authorship network of co-authors of Nikhil V. Navkar

This figure shows the co-authorship network connecting the top 25 collaborators of Nikhil V. Navkar. A scholar is included among the top collaborators of Nikhil V. Navkar 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 Nikhil V. Navkar. Nikhil V. Navkar 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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