Kailash Gopalakrishnan

52 total papers · 4.5k total citations
29 papers, 1.5k citations indexed

About

Kailash Gopalakrishnan is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Kailash Gopalakrishnan has authored 29 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Electrical and Electronic Engineering, 15 papers in Computer Vision and Pattern Recognition and 11 papers in Artificial Intelligence. Recurrent topics in Kailash Gopalakrishnan's work include Advanced Memory and Neural Computing (16 papers), Advanced Neural Network Applications (13 papers) and Adversarial Robustness in Machine Learning (6 papers). Kailash Gopalakrishnan is often cited by papers focused on Advanced Memory and Neural Computing (16 papers), Advanced Neural Network Applications (13 papers) and Adversarial Robustness in Machine Learning (6 papers). Kailash Gopalakrishnan collaborates with scholars based in United States, India and Japan. Kailash Gopalakrishnan's co-authors include Ankur Agrawal, Pritish Narayanan, Suyog Gupta, Chi On Chui, J.D. Plummer, Krishna C. Saraswat, Peter B. Griffin, Jungwook Choi, Leland Chang and Bipin Rajendran and has published in prestigious journals such as Applied Physics Letters, Journal of Applied Physics and IEEE Transactions on Electron Devices.

In The Last Decade

Kailash Gopalakrishnan

29 papers receiving 1.4k citations

Hit Papers

Deep Learning with Limite... 2015 2026 2018 2022 2015 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Kailash Gopalakrishnan 938 474 464 170 146 29 1.5k
Cheng-Xin Xue 1.5k 1.6× 131 0.3× 279 0.6× 73 0.4× 180 1.2× 28 1.6k
Ping Chi 1.3k 1.4× 365 0.8× 361 0.8× 41 0.2× 356 2.4× 23 1.6k
Zhenhua Zhu 862 0.9× 195 0.4× 266 0.6× 82 0.5× 113 0.8× 62 1.1k
Dongjoo Shin 906 1.0× 642 1.4× 341 0.7× 45 0.3× 166 1.1× 64 1.4k
Xing Hu 845 0.9× 324 0.7× 613 1.3× 133 0.8× 272 1.9× 62 1.4k
Priyanka Raina 1.3k 1.4× 451 1.0× 389 0.8× 89 0.5× 394 2.7× 64 1.8k
Tony F. Wu 1.2k 1.2× 69 0.1× 184 0.4× 261 1.5× 206 1.4× 38 1.4k
Xuan Zhang 782 0.8× 163 0.3× 280 0.6× 37 0.2× 252 1.7× 89 1.3k
Minhao Yang 970 1.0× 249 0.5× 300 0.6× 40 0.2× 56 0.4× 41 1.4k
Wei-Hao Chen 1.3k 1.4× 79 0.2× 194 0.4× 80 0.5× 152 1.0× 47 1.4k

Countries citing papers authored by Kailash Gopalakrishnan

Since Specialization
Citations

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

Fields of papers citing papers by Kailash Gopalakrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kailash Gopalakrishnan

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

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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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