Ankur P. Parikh

84 total papers · 4.7k total citations
32 papers, 2.0k citations indexed

About

Ankur P. Parikh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Ankur P. Parikh has authored 32 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Molecular Biology. Recurrent topics in Ankur P. Parikh's work include Topic Modeling (18 papers), Natural Language Processing Techniques (16 papers) and Multimodal Machine Learning Applications (6 papers). Ankur P. Parikh is often cited by papers focused on Topic Modeling (18 papers), Natural Language Processing Techniques (16 papers) and Multimodal Machine Learning Applications (6 papers). Ankur P. Parikh collaborates with scholars based in United States, India and United Kingdom. Ankur P. Parikh's co-authors include Jakob Uszkoreit, Oscar Täckström, Dipanjan Das, Tom Kwiatkowski, Kristina Toutanova, Slav Petrov, Ming‐Wei Chang, Llion Jones, Jennimaria Palomaki and Quoc V. Le and has published in prestigious journals such as Journal of the American Statistical Association, Bioinformatics and BMC Bioinformatics.

In The Last Decade

Ankur P. Parikh

28 papers receiving 1.9k citations

Hit Papers

Natural Questions: A Benc... 2016 2026 2019 2022 2019 2016 250 500 750

Author Peers

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

Author Last Decade Papers Cites
Ankur P. Parikh 1.7k 614 268 97 94 32 2.0k
Eric Huang 1.8k 1.1× 381 0.6× 248 0.9× 80 0.8× 85 0.9× 38 2.4k
Li Dong 2.3k 1.4× 640 1.0× 362 1.4× 129 1.3× 73 0.8× 63 2.8k
Kenneth Heafield 2.5k 1.5× 549 0.9× 309 1.2× 130 1.3× 162 1.7× 56 2.8k
Pierre Isabelle 2.0k 1.2× 466 0.8× 389 1.5× 50 0.5× 152 1.6× 36 2.4k
Yelong Shen 1.4k 0.8× 531 0.9× 476 1.8× 89 0.9× 69 0.7× 49 1.8k
Pengfei Liu 2.0k 1.2× 317 0.5× 235 0.9× 130 1.3× 73 0.8× 79 2.3k
Pengfei Liu 1.6k 0.9× 424 0.7× 348 1.3× 86 0.9× 83 0.9× 20 2.2k
Jakob Uszkoreit 2.5k 1.5× 1.0k 1.7× 327 1.2× 206 2.1× 109 1.2× 23 3.1k
Lifeng Shang 1.5k 0.9× 890 1.4× 250 0.9× 115 1.2× 53 0.6× 81 2.1k
Satanjeev Banerjee 2.5k 1.5× 1.1k 1.8× 340 1.3× 119 1.2× 167 1.8× 23 3.2k

Countries citing papers authored by Ankur P. Parikh

Since Specialization
Citations

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

Fields of papers citing papers by Ankur P. Parikh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ankur P. Parikh. 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 Ankur P. Parikh. The network helps show where Ankur P. Parikh may publish in the future.

Co-authorship network of co-authors of Ankur P. Parikh

This figure shows the co-authorship network connecting the top 25 collaborators of Ankur P. Parikh. A scholar is included among the top collaborators of Ankur P. Parikh 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 Ankur P. Parikh. Ankur P. Parikh 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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