Abhinav Agarwalla

1.5k total citations
2 papers, 5 citations indexed

About

Abhinav Agarwalla is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Environmental Engineering. According to data from OpenAlex, Abhinav Agarwalla has authored 2 papers receiving a total of 5 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Computer Vision and Pattern Recognition, 1 paper in Artificial Intelligence and 1 paper in Environmental Engineering. Recurrent topics in Abhinav Agarwalla's work include Advanced Vision and Imaging (1 paper), Advanced Neural Network Applications (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Abhinav Agarwalla is often cited by papers focused on Advanced Vision and Imaging (1 paper), Advanced Neural Network Applications (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). Abhinav Agarwalla collaborates with scholars based in India and United States. Abhinav Agarwalla's co-authors include Prabir Kumar Biswas, Laura Leal-Taixé, Xuhua Huang, Deva Ramanan, Francesco Ferroni, Jason Ziglar, James Hays and Aljoša Ošep and has published in prestigious journals such as .

In The Last Decade

Abhinav Agarwalla

2 papers receiving 4 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Abhinav Agarwalla India	2	2	1	1	1	1	2	5
María Cristina Castañón Bautista Mexico	2	2 1.0×					5	4
J. G. Lu China	1	2 1.0×					2	3
J. A. Gómez Netherlands	2	2 1.0×					3	4
Y. D. Cheng China	2	2 1.0×					3	4
Helge Knoop Germany	2	3 1.5×					2	4
Allan Winter Rowe Canada	2	2 1.0×					3	7
F. Sánchez Spain	2	2 1.0×					2	3
Svitlana Panina	2						4	4
Arlene Martinez United States	2						2	2
Crystal Duncan	2						2	3

Countries citing papers authored by Abhinav Agarwalla

Since Specialization

Citations

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

Fields of papers citing papers by Abhinav Agarwalla

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhinav Agarwalla

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

All Works

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2 of 2 papers shown

1.

Agarwalla, Abhinav, Xuhua Huang, Jason Ziglar, et al.. (2023). Lidar Panoptic Segmentation and Tracking without Bells and Whistles. 3 indexed citations

2.

Agarwalla, Abhinav, et al.. (2018). Unsupervised Domain Adaptation for Learning Eye Gaze from a Million Synthetic Images. 1–9. 2 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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