Joel A. Rosenfeld

798 total citations
29 papers, 422 citations indexed

About

Joel A. Rosenfeld is a scholar working on Control and Systems Engineering, Statistical and Nonlinear Physics and Computational Theory and Mathematics. According to data from OpenAlex, Joel A. Rosenfeld has authored 29 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Control and Systems Engineering, 10 papers in Statistical and Nonlinear Physics and 8 papers in Computational Theory and Mathematics. Recurrent topics in Joel A. Rosenfeld's work include Model Reduction and Neural Networks (10 papers), Adaptive Dynamic Programming Control (8 papers) and Control Systems and Identification (7 papers). Joel A. Rosenfeld is often cited by papers focused on Model Reduction and Neural Networks (10 papers), Adaptive Dynamic Programming Control (8 papers) and Control Systems and Identification (7 papers). Joel A. Rosenfeld collaborates with scholars based in United States, China and Vietnam. Joel A. Rosenfeld's co-authors include Warren E. Dixon, Rushikesh Kamalapurkar, Patrick Walters, Taylor T. Johnson, Hsi‐Yuan Chen, Teng-Hu Cheng, Zhen Kan, Weiming Xiang, Hoang-Dung Tran and Xiuying Li and has published in prestigious journals such as IEEE Transactions on Automatic Control, Journal of Computational Physics and Automatica.

In The Last Decade

Joel A. Rosenfeld

27 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joel A. Rosenfeld United States 11 206 194 150 70 48 29 422
Jason Sheng-Hong Tsai Taiwan 13 442 2.1× 64 0.3× 90 0.6× 83 1.2× 27 0.6× 56 569
Adam Czornik Poland 20 727 3.5× 233 1.2× 132 0.9× 41 0.6× 127 2.6× 101 981
Noboru Sakamoto Japan 17 436 2.1× 85 0.4× 35 0.2× 84 1.2× 15 0.3× 94 763
Salim Ibrir Saudi Arabia 17 1.1k 5.1× 88 0.5× 64 0.4× 92 1.3× 40 0.8× 85 1.1k
Mohammad Ali Nekoui Iran 14 360 1.7× 31 0.2× 76 0.5× 50 0.7× 51 1.1× 58 507
Y.T. Tsay United States 16 427 2.1× 159 0.8× 69 0.5× 74 1.1× 65 1.4× 40 698
Umberto Viaro Italy 13 434 2.1× 75 0.4× 39 0.3× 209 3.0× 54 1.1× 93 660
N. Boonsatit Thailand 10 93 0.5× 34 0.2× 97 0.6× 72 1.0× 24 0.5× 23 373
Kai Wulff Germany 9 903 4.4× 112 0.6× 37 0.2× 61 0.9× 22 0.5× 51 1.0k

Countries citing papers authored by Joel A. Rosenfeld

Since Specialization
Citations

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

Fields of papers citing papers by Joel A. Rosenfeld

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joel A. Rosenfeld. 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 Joel A. Rosenfeld. The network helps show where Joel A. Rosenfeld may publish in the future.

Co-authorship network of co-authors of Joel A. Rosenfeld

This figure shows the co-authorship network connecting the top 25 collaborators of Joel A. Rosenfeld. A scholar is included among the top collaborators of Joel A. Rosenfeld 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 Joel A. Rosenfeld. Joel A. Rosenfeld 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.
Rosenfeld, Joel A., et al.. (2024). On Convergent Dynamic Mode Decomposition and its Equivalence with Occupation Kernel Regression. IFAC-PapersOnLine. 58(17). 103–108.
2.
Rosenfeld, Joel A. & Rushikesh Kamalapurkar. (2024). Dynamic Mode Decomposition With Control Liouville Operators. IEEE Transactions on Automatic Control. 69(12). 8571–8586. 2 indexed citations
3.
Rosenfeld, Joel A., et al.. (2024). The Occupation Kernel Method for Nonlinear System Identification. SIAM Journal on Control and Optimization. 62(3). 1643–1668. 6 indexed citations
4.
Rosenfeld, Joel A. & Rushikesh Kamalapurkar. (2023). Singular Dynamic Mode Decomposition. SIAM Journal on Applied Dynamical Systems. 22(3). 2357–2381. 4 indexed citations
5.
Rosenfeld, Joel A., et al.. (2023). Dynamic Mode Decomposition of Control-Affine Nonlinear Systems Using Discrete Control Liouville Operators. IEEE Control Systems Letters. 8. 79–84.
6.
Rosenfeld, Joel A., et al.. (2023). Carleman Lifting for Nonlinear System Identification with Guaranteed Error Bounds. 2 indexed citations
7.
Rosenfeld, Joel A., et al.. (2021). Dynamic Mode Decomposition for Continuous Time Systems with the Liouville Operator. Journal of Nonlinear Science. 32(1). 17 indexed citations
8.
Rosenfeld, Joel A., et al.. (2021). Weighted Composition Operators on the Mittag-Leffler Spaces of Entire Functions. Complex Analysis and Operator Theory. 15(1). 1 indexed citations
9.
Rosenfeld, Joel A. & Rushikesh Kamalapurkar. (2021). Dynamic Mode Decomposition with Control Liouville Operators. IFAC-PapersOnLine. 54(9). 707–712. 10 indexed citations
10.
Rosenfeld, Joel A. & Warren E. Dixon. (2021). Convergence Rate Estimates for the Kernelized Predictor Corrector Method for Fractional Order Initial Value Problems. Fractional Calculus and Applied Analysis. 24(6). 1879–1898. 1 indexed citations
11.
Li, Xiuying & Joel A. Rosenfeld. (2020). Fractional Order System Identification With Occupation Kernel Regression. IEEE Control Systems Letters. 6. 19–24. 6 indexed citations
12.
Chen, Hsi‐Yuan, et al.. (2019). Approximate Optimal Motion Planning to Avoid Unknown Moving Avoidance Regions. IEEE Transactions on Robotics. 36(2). 414–430. 43 indexed citations
13.
Rosenfeld, Joel A., et al.. (2019). A mesh-free pseudospectral approach to estimating the fractional Laplacian via radial basis functions. Journal of Computational Physics. 390. 306–322. 16 indexed citations
14.
Rosenfeld, Joel A., Rushikesh Kamalapurkar, & Warren E. Dixon. (2018). The State Following Approximation Method. IEEE Transactions on Neural Networks and Learning Systems. 30(6). 1716–1730. 14 indexed citations
15.
Rosenfeld, Joel A., et al.. (2018). Approximate Dynamic Programming: Combining Regional and Local State Following Approximations. IEEE Transactions on Neural Networks and Learning Systems. 29(6). 2154–2166. 22 indexed citations
16.
Rosenfeld, Joel A., et al.. (2018). The Mittag Leffler reproducing kernel Hilbert spaces of entire and analytic functions. Journal of Mathematical Analysis and Applications. 463(2). 576–592. 14 indexed citations
17.
Xiang, Weiming, Hoang-Dung Tran, Joel A. Rosenfeld, & Taylor T. Johnson. (2018). Reachable Set Estimation and Safety Verification for Piecewise Linear Systems with Neural Network Controllers. 1574–1579. 26 indexed citations
18.
Rosenfeld, Joel A., et al.. (2018). Online Approximate Optimal Path-Planner in the Presence of Mobile Avoidance Regions. 2515–2520. 2 indexed citations
19.
Kamalapurkar, Rushikesh, Joel A. Rosenfeld, & Warren E. Dixon. (2016). Efficient model-based reinforcement learning for approximate online optimal control. Automatica. 74. 247–258. 71 indexed citations
20.
Rosenfeld, Joel A., Rushikesh Kamalapurkar, & Warren E. Dixon. (2015). State following (StaF) kernel functions for function approximation Part I: Theory and motivation. 1217–1222. 9 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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