Piyush Goyal

43 total papers · 1.3k total citations
13 papers, 677 citations indexed

About

Piyush Goyal is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Piyush Goyal has authored 13 papers receiving a total of 677 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Electrical and Electronic Engineering, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Artificial Intelligence. Recurrent topics in Piyush Goyal's work include Radiomics and Machine Learning in Medical Imaging (2 papers), COVID-19 Clinical Research Studies (1 paper) and Neurosurgical Procedures and Complications (1 paper). Piyush Goyal is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), COVID-19 Clinical Research Studies (1 paper) and Neurosurgical Procedures and Complications (1 paper). Piyush Goyal collaborates with scholars based in India, United States and Canada. Piyush Goyal's co-authors include Scott Lipnick, Andre Esteva, Ryan Poplin, Steven Finkbeiner, Ashkan Javaherian, Gaia Skibinski, Samuel Yang, D. Michael Ando, Kevan Shah and Eric Christiansen and has published in prestigious journals such as Cell, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Piyush Goyal

9 papers receiving 667 citations

Hit Papers

In Silico Labeling: Predi... 2018 2026 2020 2023 2018 100 200 300

Author Peers

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

Author Last Decade Papers Cites
Piyush Goyal 254 162 159 108 100 13 677
Yijun Su 146 0.6× 33 0.2× 314 2.0× 81 0.8× 104 1.0× 40 669
Andrey Kan 84 0.3× 371 2.3× 223 1.4× 148 1.4× 34 0.3× 23 687
Tokiya Abe 96 0.4× 56 0.3× 94 0.6× 174 1.6× 40 0.4× 49 638
Ce Wang 37 0.1× 113 0.7× 141 0.9× 70 0.6× 131 1.3× 38 787
Lauri Goodell 71 0.3× 54 0.3× 220 1.4× 117 1.1× 60 0.6× 26 619
Marcial García‐Rojo 153 0.6× 35 0.2× 109 0.7× 113 1.0× 43 0.4× 57 674
Andrew Patterson 322 1.3× 40 0.2× 365 2.3× 36 0.3× 71 0.7× 6 767
Jyrki Selinummi 317 1.2× 70 0.4× 273 1.7× 26 0.2× 85 0.8× 18 773
Brian Loranger 327 1.3× 40 0.2× 372 2.3× 32 0.3× 84 0.8× 9 727
George W. Ashdown 342 1.3× 71 0.4× 256 1.6× 18 0.2× 136 1.4× 17 738

Countries citing papers authored by Piyush Goyal

Since Specialization
Citations

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

Fields of papers citing papers by Piyush Goyal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Piyush Goyal

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