Shivkumar Sabesan

662 citations
16 papers · 495 · h-index 12

Impact in

Papers in

Shivkumar Sabesan

16 papers receiving 487 citations

Peers

Shivkumar Sabesan
Comparison fields: 5 of 61
  • Cognitive Neuroscience 321
  • Cellular and Molecular Neuroscience 196
  • Statistical and Nonlinear Physics 72
  • Neurology 65
  • Neurology 37
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Citations per year

Countries citing papers authored by Shivkumar Sabesan

Since Specialization
Citations

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

Fields of papers citing papers by Shivkumar Sabesan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Shivkumar Sabesan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shivkumar Sabesan Line = papers co-authored together Shivkumar Sabesan links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2009125
2 200757
3 200951
4 200949
5 200835
6 200532
7 201628
8 200826
9 201120
10 201518
11
Predictability of epileptic seizures: a comparative study using Lyapunov exponent and entropy based measures.
200316
12
Nonlinear dynamics of seizure prediction in a rodent model of epilepsy.
201011
13 199410
14 200510
15
Improved measure of information flow in coupled nonlinear systems
20036
16 20071

About Shivkumar Sabesan

Shivkumar Sabesan is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Computer Networks and Communications, Statistical and Nonlinear Physics and Molecular Biology, having authored 16 papers that have together received 495 indexed citations. Recurring topics across this work include Neural dynamics and brain function (10 papers), Neuroscience and Neuropharmacology Research (6 papers), EEG and Brain-Computer Interfaces (5 papers), stochastic dynamics and bifurcation (4 papers), Nonlinear Dynamics and Pattern Formation (3 papers), Photoreceptor and optogenetics research (2 papers), Neural Networks and Applications (2 papers) and Epilepsy research and treatment (1 paper). The work is most often cited by research in Cognitive Neuroscience (321 citations), Cellular and Molecular Neuroscience (196 citations), Statistical and Nonlinear Physics (72 citations), Neurology (65 citations) and Neurology (37 citations). Shivkumar Sabesan has collaborated with scholars based in United States, Sweden and Australia. Frequent co-authors include Leonidas Iasemidis, K. Tsakalis, Niranjan Chakravarthy, David M. Treiman, Levi B. Good, Andreas Spanias, Awadhesh Prasad, Konstantinos Tsakalis, Raman Sankar and Maryam Ravan. Their work appears in journals such as International Journal of Neural Systems, Journal of Combinatorial Optimization, Epilepsy & Behavior, Epilepsia and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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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