Ashvin Nair

1.3k total citations
4 papers, 181 citations indexed

About

Ashvin Nair is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ashvin Nair has authored 4 papers receiving a total of 181 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Artificial Intelligence, 2 papers in Control and Systems Engineering and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ashvin Nair's work include Reinforcement Learning in Robotics (3 papers), Robot Manipulation and Learning (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Ashvin Nair is often cited by papers focused on Reinforcement Learning in Robotics (3 papers), Robot Manipulation and Learning (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). Ashvin Nair collaborates with scholars based in United States and Germany. Ashvin Nair's co-authors include Sergey Levine, Jitendra Malik, Pieter Abbeel, Pulkit Agrawal, Steven Lin, Vitchyr H. Pong, Murtaza Dalal, Shikhar Bahl, Eugen Solowjow and B. X. Zhu and has published in prestigious journals such as arXiv (Cornell University), Neural Information Processing Systems and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

Ashvin Nair

4 papers receiving 171 citations

Peers

Ashvin Nair
Mohi Khansari United States
Toki Migimatsu United States
Nikolay Jetchev Germany
Alex Irpan United States
Arthur Bucker United Kingdom
Florian Golemo Canada
Jennifer E. King United States
Kendall Lowrey United States
S. Reza Ahmadzadeh United States
Oier Mees Germany
Mohi Khansari United States
Ashvin Nair
Citations per year, relative to Ashvin Nair Ashvin Nair (= 1×) peers Mohi Khansari

Countries citing papers authored by Ashvin Nair

Since Specialization
Citations

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

Fields of papers citing papers by Ashvin Nair

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ashvin Nair

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

All Works

4 of 4 papers shown
1.
2.
Fang, Kuan, et al.. (2022). Planning to Practice: Efficient Online Fine-Tuning by Composing Goals in Latent Space. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 4076–4083. 7 indexed citations
3.
Nair, Ashvin, Vitchyr H. Pong, Murtaza Dalal, et al.. (2018). Visual Reinforcement Learning with Imagined Goals. arXiv (Cornell University). 31. 9191–9200. 38 indexed citations
4.
Agrawal, Pulkit, Ashvin Nair, Pieter Abbeel, Jitendra Malik, & Sergey Levine. (2016). Learning to poke by poking: experiential learning of intuitive physics. Neural Information Processing Systems. 29. 5092–5100. 128 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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2026