Pratik Chaudhari

173 total papers · 1.3k total citations
40 papers, 458 citations indexed

About

Pratik Chaudhari is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Pratik Chaudhari has authored 40 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 8 papers in Control and Systems Engineering. Recurrent topics in Pratik Chaudhari's work include Robotic Path Planning Algorithms (8 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Target Tracking and Data Fusion in Sensor Networks (4 papers). Pratik Chaudhari is often cited by papers focused on Robotic Path Planning Algorithms (8 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Target Tracking and Data Fusion in Sensor Networks (4 papers). Pratik Chaudhari collaborates with scholars based in United States, India and Italy. Pratik Chaudhari's co-authors include Christos Davatzikos, Rongguang Wang, Stefano Soatto, Yann LeCun, Carlo Baldassi, Riccardo Zecchina, Christian Borgs, Levent Sagun, Jennifer Chayes and Anna Choromanska and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Mechanical Systems and Signal Processing and IEEE Transactions on Robotics.

In The Last Decade

Pratik Chaudhari

35 papers receiving 445 citations

Author Peers

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

Author Last Decade Papers Cites
Pratik Chaudhari 220 152 48 47 45 40 458
Yanjie Li 108 0.5× 193 1.3× 81 1.7× 42 0.9× 49 1.1× 62 540
Hui Li 99 0.5× 221 1.5× 35 0.7× 44 0.9× 21 0.5× 36 413
Erkan Tanyıldızı 229 1.0× 122 0.8× 75 1.6× 8 0.2× 75 1.7× 33 527
Mukul Sutaone 122 0.6× 161 1.1× 29 0.6× 11 0.2× 15 0.3× 66 480
Ling He 146 0.7× 75 0.5× 168 3.5× 32 0.7× 12 0.3× 25 505
Nikolay Nagornov 154 0.7× 137 0.9× 35 0.7× 7 0.1× 58 1.3× 29 533
Zhi-Kai Huang 88 0.4× 223 1.5× 25 0.5× 60 1.3× 11 0.2× 54 540
Cheng Liu 118 0.5× 209 1.4× 169 3.5× 28 0.6× 44 1.0× 31 540
Peng Chen 131 0.6× 68 0.4× 87 1.8× 12 0.3× 28 0.6× 81 537
Yan Zhou 167 0.8× 218 1.4× 52 1.1× 20 0.4× 14 0.3× 75 479

Countries citing papers authored by Pratik Chaudhari

Since Specialization
Citations

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

Fields of papers citing papers by Pratik Chaudhari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pratik Chaudhari

This figure shows the co-authorship network connecting the top 25 collaborators of Pratik Chaudhari. A scholar is included among the top collaborators of Pratik Chaudhari 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 Pratik Chaudhari. Pratik Chaudhari 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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2026