Sunil L. Kukreja

1.2k total citations
64 papers, 895 citations indexed

About

Sunil L. Kukreja is a scholar working on Control and Systems Engineering, Biomedical Engineering and Civil and Structural Engineering. According to data from OpenAlex, Sunil L. Kukreja has authored 64 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Control and Systems Engineering, 16 papers in Biomedical Engineering and 15 papers in Civil and Structural Engineering. Recurrent topics in Sunil L. Kukreja's work include Control Systems and Identification (27 papers), Fault Detection and Control Systems (18 papers) and Probabilistic and Robust Engineering Design (15 papers). Sunil L. Kukreja is often cited by papers focused on Control Systems and Identification (27 papers), Fault Detection and Control Systems (18 papers) and Probabilistic and Robust Engineering Design (15 papers). Sunil L. Kukreja collaborates with scholars based in United States, Singapore and Canada. Sunil L. Kukreja's co-authors include Nitish V. Thakor, Martin Brenner, Johan Löfberg, Robert E. Kearney, Henrietta L. Galiana, Wang Wei Lee, Chen‐Hua Yeow, Hongliang Ren, Jin-Huat Low and Phone May Khin and has published in prestigious journals such as Contemporary Sociology A Journal of Reviews, NeuroImage and Journal of neurosurgery.

In The Last Decade

Sunil L. Kukreja

61 papers receiving 860 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sunil L. Kukreja United States 16 312 297 203 125 95 64 895
Lena Zentner Germany 16 309 1.0× 228 0.8× 104 0.5× 147 1.2× 220 2.3× 71 774
Marco P. Schoen United States 14 251 0.8× 496 1.7× 275 1.4× 85 0.7× 75 0.8× 107 1.0k
R. Tomović Serbia 16 405 1.3× 414 1.4× 122 0.6× 60 0.5× 314 3.3× 50 1.1k
Qiang Gao China 23 307 1.0× 140 0.5× 584 2.9× 174 1.4× 184 1.9× 133 1.5k
N.B. Jones United Kingdom 17 212 0.7× 347 1.2× 145 0.7× 171 1.4× 97 1.0× 88 1.1k
Vincenzo Niola Italy 14 124 0.4× 427 1.4× 183 0.9× 53 0.4× 130 1.4× 75 781
Yanfei Zhu China 14 141 0.5× 99 0.3× 48 0.2× 262 2.1× 88 0.9× 65 829
Ke Li China 17 176 0.6× 80 0.3× 311 1.5× 119 1.0× 124 1.3× 93 1.1k
Michele Basso Italy 15 175 0.6× 199 0.7× 24 0.1× 188 1.5× 85 0.9× 83 1.2k
Tangfei Tao China 15 283 0.9× 114 0.4× 43 0.2× 94 0.8× 348 3.7× 56 829

Countries citing papers authored by Sunil L. Kukreja

Since Specialization
Citations

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

Fields of papers citing papers by Sunil L. Kukreja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sunil L. Kukreja. 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 Sunil L. Kukreja. The network helps show where Sunil L. Kukreja may publish in the future.

Co-authorship network of co-authors of Sunil L. Kukreja

This figure shows the co-authorship network connecting the top 25 collaborators of Sunil L. Kukreja. A scholar is included among the top collaborators of Sunil L. Kukreja 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 Sunil L. Kukreja. Sunil L. Kukreja 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.
Yi, Chen, et al.. (2018). An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition. IEEE Transactions on Biomedical Circuits and Systems. 12(2). 313–325. 70 indexed citations
2.
Kumar, Kirthika Senthil, et al.. (2017). Development of flexible fabric based tactile sensor for closed loop control of soft robotic actuator. 1451–1456. 16 indexed citations
3.
Lee, Wang Wei, Sunil L. Kukreja, & Nitish V. Thakor. (2017). Discrimination of Dynamic Tactile Contact by Temporally Precise Event Sensing in Spiking Neuromorphic Networks. Frontiers in Neuroscience. 11. 5–5. 23 indexed citations
4.
Mishra, Abhishek, et al.. (2017). A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors. Frontiers in Neuroscience. 11. 83–83. 12 indexed citations
5.
Mishra, Abhishek, et al.. (2016). Real-time robot tracking and following with neuromorphic vision sensor. 9. 13–18. 4 indexed citations
6.
Caliò, Renato, et al.. (2016). Design and preliminary evaluation of haptic devices for upper limb stimulation and integration within a virtual reality cave. CINECA IRIS Institutional Research Information System (Sant'Anna School of Advanced Studies). 20. 464–469. 4 indexed citations
7.
8.
Aljanaideh, Khaled F., et al.. (2012). Sensor-to-Sensor Identification for the SOFIA Testbed. AIAA Guidance, Navigation, and Control Conference. 7 indexed citations
9.
Kukreja, Sunil L., et al.. (2012). A sparse matrix approach for simultaneous quantification of nystagmus and saccade. PubMed. 17. 5478–5481.
10.
Aljanaideh, Khaled F., et al.. (2012). Sensor-to-sensor identification of Hammerstein systems. 123. 2846–2851. 1 indexed citations
11.
Moulin, Boris, Jie Zeng, & Sunil L. Kukreja. (2011). Experimental Model Based Robust Aeroservoelastic Control for the S4T Wind-Tunnel Model. AIAA Atmospheric Flight Mechanics Conference. 1 indexed citations
12.
Danowsky, Brian P., Paul M. Thompson, & Sunil L. Kukreja. (2010). Using Describing Functions for Limit-Cycle-Oscillation Analysis Applied to Aeroservoelastic Models with Free-Play. 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. 5 indexed citations
13.
Kukreja, Sunil L.. (2008). Non-Linear System Identification for Aeroelastic Systems with Application to Experimental Data. AIAA Guidance, Navigation and Control Conference and Exhibit. 3 indexed citations
14.
Kukreja, Sunil L. & Martin Brenner. (2007). Nonlinear Black-Box Modeling of Aeroelastic Systems Using Structure Detection Approach: Application to F/A-18 Aircraft Data. Journal of Guidance Control and Dynamics. 30(2). 557–564. 7 indexed citations
15.
Kukreja, Sunil L., Johan Löfberg, & Martin Brenner. (2006). A LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATOR (LASSO) FOR NONLINEAR SYSTEM IDENTIFICATION. IFAC Proceedings Volumes. 39(1). 814–819. 155 indexed citations
16.
Kukreja, Sunil L.. (2005). A suboptimal bootstrap method for structure detection of non-linear output-error models with application to human ankle dynamics. International Journal of Control. 78(12). 937–948. 4 indexed citations
17.
Kukreja, Sunil L., Robert E. Kearney, & Henrietta L. Galiana. (2005). A Least-Squares Parameter Estimation Algorithm for Switched Hammerstein Systems With Applications to the VOR. IEEE Transactions on Biomedical Engineering. 52(3). 431–444. 48 indexed citations
18.
Kukreja, Sunil L., Henrietta L. Galiana, & Robert E. Kearney. (2004). A bootstrap method for structure detection of NARMAX models. International Journal of Control. 77(2). 132–143. 28 indexed citations
19.
Kukreja, Sunil L. & Roger N. Gunn. (2004). Bootstrapped DEPICT for error estimation in PET functional imaging. NeuroImage. 21(3). 1096–1104. 12 indexed citations
20.
Kukreja, Sunil L., Henrietta L. Galiana, & Robert E. Kearney. (2003). Structure detection of NARMAX models using bootstrap methods. 1. 1071–1076. 13 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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