Vaishnavh Nagarajan

506 total citations
7 papers, 44 citations indexed

About

Vaishnavh Nagarajan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Economics and Econometrics. According to data from OpenAlex, Vaishnavh Nagarajan has authored 7 papers receiving a total of 44 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 2 papers in Economics and Econometrics. Recurrent topics in Vaishnavh Nagarajan's work include Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Bacillus and Francisella bacterial research (1 paper). Vaishnavh Nagarajan is often cited by papers focused on Advanced Neural Network Applications (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Bacillus and Francisella bacterial research (1 paper). Vaishnavh Nagarajan collaborates with scholars based in United States, India and Canada. Vaishnavh Nagarajan's co-authors include J. Zico Kolter, Hemank Lamba, Kijung Shin, Leandro Soriano Marcolino, Garth A. Gibson, Milind Tambe, Gregory R. Ganger and Pradeep Ravikumar and has published in prestigious journals such as USENIX Annual Technical Conference, arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Vaishnavh Nagarajan

7 papers receiving 41 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Vaishnavh Nagarajan United States	4	26	12	11	10	6	7	44
Michał Dereziński United States	4	24 0.9×	2 0.2×	10 0.9×	12 1.2×		18	43
Amir Niknejad United States	3	7 0.3×	6 0.5×	7 0.6×	9 0.9×		6	40
Richard Lawrence United States	3	14 0.5×		6 0.5×	3 0.3×	4 0.7×	6	28
Hongzhou Lin United States	4	17 0.7×		10 0.9×	9 0.9×	6 1.0×	8	42
Amir Hosein Khasahmadi United States	3	32 1.2×		20 1.8×	14 1.4×	6 1.0×	5	52
Behrooz Ghorbani United States	4	47 1.8×	1 0.1×	18 1.6×	6 0.6×	11 1.8×	6	57
Hippolyt Ritter United Kingdom	3	87 3.3×	2 0.2×	42 3.8×	7 0.7×	4 0.7×	7	99
Gary Bécigneul Switzerland	5	47 1.8×	1 0.1×	22 2.0×	11 1.1×	7 1.2×	8	63
I. Babuschkin United States	3	45 1.7×		16 1.5×	3 0.3×	5 0.8×	6	66
Aymeric Dieuleveut France	4	38 1.5×		6 0.5×	17 1.7×	3 0.5×	12	56

Countries citing papers authored by Vaishnavh Nagarajan

Since Specialization

Citations

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

Fields of papers citing papers by Vaishnavh Nagarajan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vaishnavh Nagarajan

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

All Works

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7 of 7 papers shown

1.

Nagarajan, Vaishnavh, et al.. (2019). Revisiting Adversarial Risk. International Conference on Artificial Intelligence and Statistics. 2331–2339. 1 indexed citations

2.

Nagarajan, Vaishnavh & J. Zico Kolter. (2019). Uniform convergence may be unable to explain generalization in deep learning. Neural Information Processing Systems. 32. 11611–11622. 12 indexed citations

3.

Nagarajan, Vaishnavh & J. Zico Kolter. (2019). Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience. arXiv (Cornell University). 9 indexed citations

4.

Nagarajan, Vaishnavh, et al.. (2018). Geriatrix: aging what you see and what you don't see a file system aging approach for modern storage systems. USENIX Annual Technical Conference. 691–703. 4 indexed citations

5.

Lamba, Hemank, et al.. (2016). Incorporating Side Information in Tensor Completion. 65–66. 15 indexed citations

6.

Nagarajan, Vaishnavh, Leandro Soriano Marcolino, & Milind Tambe. (2015). Every Team Deserves a Second Chance: Identifying when Things Go Wrong. Adaptive Agents and Multi-Agents Systems. 695–703. 1 indexed citations

7.

Nagarajan, Vaishnavh, Leandro Soriano Marcolino, & Milind Tambe. (2015). Every Team Deserves a Second Chance: Identifying When Things Go Wrong (Student Abstract Version). Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 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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