Priya Goyal

40.7k total citations · 1 hit paper
9 papers, 6.3k citations indexed

About

Priya Goyal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Priya Goyal has authored 9 papers receiving a total of 6.3k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Computer Vision and Pattern Recognition, 4 papers in Artificial Intelligence and 3 papers in Computer Networks and Communications. Recurrent topics in Priya Goyal's work include Domain Adaptation and Few-Shot Learning (3 papers), Parallel Computing and Optimization Techniques (2 papers) and Advanced Neural Network Applications (2 papers). Priya Goyal is often cited by papers focused on Domain Adaptation and Few-Shot Learning (3 papers), Parallel Computing and Optimization Techniques (2 papers) and Advanced Neural Network Applications (2 papers). Priya Goyal collaborates with scholars based in India, United States and Israel. Priya Goyal's co-authors include Tsung-Yi Lin, Ross Girshick, Piotr Dollár, Kaiming He, Matthijs Douze, Andrew Adams, Albert Cohen, Oleksandr Zinenko, William S. Moses and Zachary DeVito and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, ACM Transactions on Architecture and Code Optimization and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Priya Goyal

7 papers receiving 6.1k citations

Hit Papers

Focal Loss for Dense Object Detection 2018 2026 2020 2023 2018 2.0k 4.0k 6.0k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Priya Goyal India 5 3.2k 1.6k 742 676 671 9 6.3k
Hanzi Mao United States 5 3.8k 1.2× 1.9k 1.2× 606 0.8× 869 1.3× 866 1.3× 8 7.8k
Qilong Wang China 21 4.3k 1.3× 1.9k 1.2× 648 0.9× 1.2k 1.8× 575 0.9× 67 7.3k
Daquan Zhou China 11 2.8k 0.9× 943 0.6× 559 0.8× 740 1.1× 366 0.5× 29 4.9k
Zhuang Liu China 16 4.5k 1.4× 2.7k 1.7× 537 0.7× 756 1.1× 706 1.1× 27 7.5k
Peihua Li China 29 4.6k 1.4× 1.9k 1.2× 742 1.0× 1.2k 1.8× 603 0.9× 118 8.2k
Mingxing Tan United States 16 4.2k 1.3× 1.2k 0.8× 998 1.3× 735 1.1× 332 0.5× 43 6.6k
Zhenhua Wang China 15 2.6k 0.8× 1.4k 0.9× 646 0.9× 399 0.6× 422 0.6× 50 6.0k
Song Bai China 42 5.6k 1.8× 2.4k 1.5× 855 1.2× 691 1.0× 424 0.6× 115 8.1k
Lingxi Xie China 36 5.5k 1.7× 2.8k 1.8× 796 1.1× 689 1.0× 563 0.8× 119 8.2k
Chunjing Xu China 23 4.4k 1.4× 1.4k 0.9× 588 0.8× 1.2k 1.7× 284 0.4× 63 6.3k

Countries citing papers authored by Priya Goyal

Since Specialization
Citations

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

Fields of papers citing papers by Priya Goyal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Priya Goyal

This figure shows the co-authorship network connecting the top 25 collaborators of Priya Goyal. A scholar is included among the top collaborators of Priya 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 Priya Goyal. Priya Goyal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Goyal, Priya, et al.. (2025). Telemedicine for the detection and management of in-hospital and out-of-hospital sudden cardiac arrest: Status quo and quo vadis. American Heart Journal Plus Cardiology Research and Practice. 59. 100600–100600.
3.
Williams, Samuel, et al.. (2023). Performance Portability Evaluation of Blocked Stencil Computations on GPUs. eScholarship (California Digital Library). 1007–1018. 10 indexed citations
4.
Goyal, Priya, et al.. (2022). A Self-Supervised Descriptor for Image Copy Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 14512–14522. 29 indexed citations
5.
Goyal, Priya, Adriana Romero, Caner Hazırbaş, Levent Sagun, & Nicolas Usunier. (2022). Fairness Indicators for Systematic Assessments of Visual Feature Extractors. 70–88. 8 indexed citations
6.
Vasilache, Nicolas, Oleksandr Zinenko, Priya Goyal, et al.. (2019). The Next 700 Accelerated Layers. ACM Transactions on Architecture and Code Optimization. 16(4). 1–26. 29 indexed citations
7.
Lin, Tsung-Yi, Priya Goyal, Ross Girshick, Kaiming He, & Piotr Dollár. (2018). Focal Loss for Dense Object Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(2). 318–327. 6233 indexed citations breakdown →
8.
Goyal, Priya, et al.. (2016). An efficient spectrum hole utilization for transmission in Cognitive Radio Networks. 57. 322–327. 3 indexed citations
9.
Goyal, Priya, et al.. (2015). A Study on 5G Evolution and Revolution. 3 indexed citations

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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