Nikunj Saunshi

6 papers and 105 indexed citations i.

About

Nikunj Saunshi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Nikunj Saunshi has authored 6 papers receiving a total of 105 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Signal Processing. Recurrent topics in Nikunj Saunshi’s work include Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Nikunj Saunshi is often cited by papers focused on Topic Modeling (4 papers), Natural Language Processing Techniques (4 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Nikunj Saunshi collaborates with scholars based in United States and Israel. Nikunj Saunshi's co-authors include Mikhail Khodak, Sanjeev Arora, Kiran Vodrahalli, Tengyu Ma, Yingyu Liang, Brandon Stewart and Orestis Plevrakis and has published in prestigious journals such as Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Co-authorship network of co-authors of Nikunj Saunshi i

Fields of papers citing papers by Nikunj Saunshi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Nikunj Saunshi

Since Specialization
Citations

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

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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2025