Nikita Jain

153 total papers · 2.0k total citations
83 papers, 1.3k citations indexed

About

Nikita Jain is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Nikita Jain has authored 83 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 11 papers in Molecular Biology. Recurrent topics in Nikita Jain's work include Anomaly Detection Techniques and Applications (6 papers), AI in cancer detection (4 papers) and Medical Image Segmentation Techniques (4 papers). Nikita Jain is often cited by papers focused on Anomaly Detection Techniques and Applications (6 papers), AI in cancer detection (4 papers) and Medical Image Segmentation Techniques (4 papers). Nikita Jain collaborates with scholars based in India, United States and Malaysia. Nikita Jain's co-authors include D. Jude Hemanth, Rachna Jain, Akshay Aggarwal, Vedika Gupta, Deepali Virmani, Senthilkumar Mohan, Ali Ahmadian, Andrew J. Westwood, Массимилиано Феррара and Sudha Seshadri and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Nikita Jain

74 papers receiving 1.2k citations

Hit Papers

Convolutional neural netw... 2019 2026 2021 2023 2019 50 100 150 200 250

Author Peers

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

Author Last Decade Papers Cites
Nikita Jain 419 261 224 170 157 83 1.3k
Mohammed Zakariah 532 1.3× 399 1.5× 210 0.9× 145 0.9× 71 0.5× 90 1.5k
Yuanpeng Zhang 440 1.1× 172 0.7× 84 0.4× 162 1.0× 443 2.8× 112 1.6k
Il-Seok Oh 778 1.9× 678 2.6× 150 0.7× 128 0.8× 134 0.9× 61 1.8k
Xiaoxiao Li 585 1.4× 126 0.5× 120 0.5× 304 1.8× 108 0.7× 52 1.3k
Νικόλαος Γιαννακέας 293 0.7× 116 0.4× 121 0.5× 147 0.9× 150 1.0× 116 1.6k
Gaurav Gupta 364 0.9× 241 0.9× 168 0.8× 218 1.3× 110 0.7× 88 1.4k
William Speier 461 1.1× 180 0.7× 87 0.4× 380 2.2× 188 1.2× 90 1.8k
Youyong Kong 510 1.2× 388 1.5× 118 0.5× 293 1.7× 86 0.5× 105 1.8k
Maryam Panahiazar 347 0.8× 109 0.4× 100 0.4× 141 0.8× 165 1.1× 36 1.2k
Gurvinder Singh 571 1.4× 134 0.5× 60 0.3× 139 0.8× 40 0.3× 115 1.4k

Countries citing papers authored by Nikita Jain

Since Specialization
Citations

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

Fields of papers citing papers by Nikita Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nikita Jain

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