Kush Bhatia

957 total citations
12 papers, 341 citations indexed

About

Kush Bhatia is a scholar working on Artificial Intelligence, Statistics and Probability and Computational Mechanics. According to data from OpenAlex, Kush Bhatia has authored 12 papers receiving a total of 341 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 5 papers in Statistics and Probability and 3 papers in Computational Mechanics. Recurrent topics in Kush Bhatia's work include Sparse and Compressive Sensing Techniques (3 papers), Machine Learning and Algorithms (3 papers) and Statistical Methods and Inference (3 papers). Kush Bhatia is often cited by papers focused on Sparse and Compressive Sensing Techniques (3 papers), Machine Learning and Algorithms (3 papers) and Statistical Methods and Inference (3 papers). Kush Bhatia collaborates with scholars based in United States, India and Switzerland. Kush Bhatia's co-authors include Purushottam Kar, Prateek Jain, Manik Varma, Himanshu Jain, Anca D. Dragan, Sandy H. Huang, Pieter Abbeel, Peter L. Bartlett, Prateek Jain and Ashwin Pananjady and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Computer Vision and Image Understanding.

In The Last Decade

Kush Bhatia

10 papers receiving 329 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kush Bhatia United States	6	279	78	44	41	33	12	341
Jürgen Beringer Germany	5	265 0.9×	76 1.0×	30 0.7×	13 0.3×	21 0.6×	5	308
Ching-pei Lee Taiwan	7	144 0.5×	72 0.9×	70 1.6×	5 0.1×	26 0.8×	13	266
Yevgeny Seldin Germany	10	215 0.8×	25 0.3×	12 0.3×	20 0.5×	9 0.3×	30	266
Mitchell Stern United States	8	438 1.6×	133 1.7×	106 2.4×	6 0.1×	8 0.2×	11	520
Boulos Harb United States	8	249 0.9×	92 1.2×	79 1.8×	3 0.1×	34 1.0×	17	335
Yu Yan China	10	339 1.2×	92 1.2×	39 0.9×	15 0.4×	8 0.2×	27	446
Ian En-Hsu Yen United States	10	279 1.0×	92 1.2×	60 1.4×	5 0.1×	13 0.4×	24	327
Xuan Hong Dang Australia	7	237 0.8×	49 0.6×	38 0.9×	9 0.2×	14 0.4×	15	274

Countries citing papers authored by Kush Bhatia

Since Specialization

Citations

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

Fields of papers citing papers by Kush Bhatia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kush Bhatia

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

All Works

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12 of 12 papers shown

Bhatia, Kush, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, & Michael I. Jordan. (2023). Bayesian Robustness: A Nonasymptotic Viewpoint. Journal of the American Statistical Association. 119(546). 1112–1123.

Huang, Sandy H., Kush Bhatia, Pieter Abbeel, et al.. (2021). Explaining robot policies. SHILAP Revista de lepidopterología. 2(4). 3 indexed citations

Bhatia, Kush, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, & Martin J. Wainwright. (2021). Preference learning along multiple criteria: A game-theoretic perspective. arXiv (Cornell University). 33. 7413–7424.

Bhatia, Kush, et al.. (2019). Adaptive Hard Thresholding for Near-optimal Consistent Robust Regression. Conference on Learning Theory. 2892–2897. 1 indexed citations

Abbasi-Yadkori, Yasin, et al.. (2019). Politex: Regret Bounds for Policy Iteration using Expert Prediction. International Conference on Machine Learning. 3692–3702. 11 indexed citations

Bhatia, Kush, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, & Michael I. Jordan. (2018). Gen-Oja: Simple & Efficient Algorithm for Streaming Generalized Eigenvector Computation. arXiv (Cornell University). 31. 7016–7025. 1 indexed citations

Huang, Sandy H., Kush Bhatia, Pieter Abbeel, & Anca D. Dragan. (2018). Establishing Appropriate Trust via Critical States. 3929–3936. 51 indexed citations

Pananjady, Ashwin, et al.. (2018). Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems. arXiv (Cornell University). 21(21). 1–2925. 50 indexed citations

Bhatia, Kush, Prateek Jain, Parameswaran Kamalaruban, & Purushottam Kar. (2017). Consistent Robust Regression. Neural Information Processing Systems. 30. 2110–2119. 15 indexed citations

10.

Bhatia, Kush, et al.. (2016). Lazy Generic Cuts. Computer Vision and Image Understanding. 143. 80–91. 5 indexed citations

11.

Bhatia, Kush, Himanshu Jain, Purushottam Kar, Manik Varma, & Prateek Jain. (2015). Sparse local embeddings for extreme multi-label classification. Neural Information Processing Systems. 28. 730–738. 176 indexed citations

12.

Bhatia, Kush, Prateek Jain, & Purushottam Kar. (2015). Robust Regression via Hard Thresholding. arXiv (Cornell University). 28. 721–729. 28 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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Breakdown of academic impact, for papers by Jürgen Beringer Breakdown of academic impact, for papers by Ching-pei Lee Breakdown of academic impact, for papers by Yevgeny Seldin Breakdown of academic impact, for papers by Mitchell Stern Breakdown of academic impact, for papers by Boulos Harb Breakdown of academic impact, for papers by Yu Yan Breakdown of academic impact, for papers by Ian En-Hsu Yen Breakdown of academic impact, for papers by Xuan Hong Dang