Vignesh Narayanan

771 total citations
53 papers, 573 citations indexed

About

Vignesh Narayanan is a scholar working on Computational Theory and Mathematics, Control and Systems Engineering and Artificial Intelligence. According to data from OpenAlex, Vignesh Narayanan has authored 53 papers receiving a total of 573 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Computational Theory and Mathematics, 27 papers in Control and Systems Engineering and 22 papers in Artificial Intelligence. Recurrent topics in Vignesh Narayanan's work include Adaptive Dynamic Programming Control (29 papers), Adaptive Control of Nonlinear Systems (19 papers) and Stability and Control of Uncertain Systems (13 papers). Vignesh Narayanan is often cited by papers focused on Adaptive Dynamic Programming Control (29 papers), Adaptive Control of Nonlinear Systems (19 papers) and Stability and Control of Uncertain Systems (13 papers). Vignesh Narayanan collaborates with scholars based in United States, India and Spain. Vignesh Narayanan's co-authors include S. Jagannathan, Avimanyu Sahoo, K. Ramkumar, Koshy George, Jr-Shin Li, Hamidreza Modares, Frank L. Lewis, Yu Zhang, Subbarao Kambhampati and S. Jagannathan and has published in prestigious journals such as IEEE Transactions on Automatic Control, Scientific Reports and IEEE Transactions on Industrial Electronics.

In The Last Decade

Vignesh Narayanan

48 papers receiving 563 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vignesh Narayanan United States 11 326 321 169 145 125 53 573
Yuling Liang China 12 269 0.8× 212 0.7× 93 0.6× 163 1.1× 78 0.6× 28 459
Yanwei Zhao China 7 220 0.7× 123 0.4× 71 0.4× 160 1.1× 54 0.4× 7 373
Justin R. Klotz United States 13 381 1.2× 96 0.3× 51 0.3× 457 3.2× 83 0.7× 23 703
Zhijian Cheng China 6 414 1.3× 111 0.3× 93 0.6× 290 2.0× 64 0.5× 13 548
Carlo Savorgnan Italy 13 272 0.8× 76 0.2× 41 0.2× 54 0.4× 51 0.4× 24 446
Yingjiang Zhou China 13 267 0.8× 72 0.2× 68 0.4× 287 2.0× 64 0.5× 48 479
Gunther Reißig Germany 13 218 0.7× 184 0.6× 35 0.2× 51 0.4× 37 0.3× 43 383
Ker‐Wei Yu Taiwan 12 417 1.3× 68 0.2× 90 0.5× 268 1.8× 54 0.4× 35 644

Countries citing papers authored by Vignesh Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by Vignesh Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vignesh Narayanan

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

All Works

20 of 20 papers shown
1.
Narayanan, Vignesh, et al.. (2025). Iterative Reservoir Computing Networks for Reconstructing Irregular Time Series. IEEE Transactions on Neural Networks and Learning Systems. 36(8). 14189–14200. 1 indexed citations
2.
Narayanan, Vignesh, Wei Zhang, & Jr-Shin Li. (2024). Duality of Ensemble Systems Through Moment Representations. IEEE Transactions on Automatic Control. 69(10). 7270–7276. 1 indexed citations
3.
4.
Geiger, M., Vignesh Narayanan, & S. Jagannathan. (2024). Optimal Tracking of Uncertain Linear Discrete-Time Systems Using Trajectory-Dependent Lifelong Q-learning. 3631–3636.
5.
Jagannathan, S., Vignesh Narayanan, & Avimanyu Sahoo. (2024). Optimal Event-Triggered Control Using Adaptive Dynamic Programming. 1 indexed citations
6.
Roy, Kaushik, et al.. (2024). Causal Event Graph-Guided Language-based Spatiotemporal Question Answering. Proceedings of the AAAI Symposium Series. 3(1). 227–233.
7.
Narayanan, Vignesh, et al.. (2024). Expressive and Flexible Simulation of Information Spread Strategies in Social Networks Using Planning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(21). 23820–23822.
8.
Narayanan, Vignesh, et al.. (2024). Exploring Alternative Approaches to Language Modeling for Learning from Data and Knowledge. Proceedings of the AAAI Symposium Series. 3(1). 279–286.
9.
Roy, Kaushik, et al.. (2023). Process Knowledge-Infused Learning for Clinician-Friendly Explanations. Proceedings of the AAAI Symposium Series. 1(1). 154–160. 4 indexed citations
10.
Pallagani, Vishal, et al.. (2023). On safe and usable chatbots for promoting voter participation. AI Magazine. 44(3). 240–247. 1 indexed citations
11.
Narayanan, Vignesh, Brett W. Robertson, Andrea Hickerson, Biplav Srivastava, & Bryant Walker Smith. (2021). Securing social media for seniors from information attacks: Modeling, detecting, intervening, and communicating risks. 297–302. 3 indexed citations
12.
Narayanan, Vignesh, et al.. (2020). Learning to Control Neurons using Aggregated Measurements. PubMed. 2020. 4028–4033. 3 indexed citations
13.
Narayanan, Vignesh, et al.. (2020). Parallel residual projection: a new paradigm for solving linear inverse problems. Scientific Reports. 10(1). 12846–12846. 1 indexed citations
14.
Sahoo, Avimanyu & Vignesh Narayanan. (2019). Optimization of sampling intervals for tracking control of nonlinear systems: A game theoretic approach. Neural Networks. 114. 78–90. 10 indexed citations
15.
Narayanan, Vignesh, Jr-Shin Li, & ShiNung Ching. (2019). Biophysically interpretable inference of single neuron dynamics. Journal of Computational Neuroscience. 47(1). 61–76. 3 indexed citations
16.
Narayanan, Vignesh, Avimanyu Sahoo, S. Jagannathan, & Koshy George. (2018). Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Event-Triggered Nonzero-Sum Games. IEEE Transactions on Neural Networks and Learning Systems. 30(5). 1512–1522. 60 indexed citations
17.
Narayanan, Vignesh, S. Jagannathan, & K. Ramkumar. (2018). Event-Sampled Output Feedback Control of Robot Manipulators Using Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 30(6). 1651–1658. 56 indexed citations
18.
Narayanan, Vignesh, et al.. (2017). Event-Sampled Direct Adaptive NN Output- and State-Feedback Control of Uncertain Strict-Feedback System. IEEE Transactions on Neural Networks and Learning Systems. 29(5). 1850–1863. 58 indexed citations
19.
Narayanan, Vignesh & S. Jagannathan. (2016). Distributed adaptive optimal regulation of uncertain large‐scale interconnected systems using hybrid Q‐learning approach. IET Control Theory and Applications. 10(12). 1448–1457. 18 indexed citations
20.
Zhang, Yu, Vignesh Narayanan, Tathagata Chakraborti, & Subbarao Kambhampati. (2015). A human factors analysis of proactive support in human-robot teaming. 3586–3593. 29 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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