Marcos Netto

2.1k total citations · 2 hit papers
18 papers, 1.4k citations indexed

About

Marcos Netto is a scholar working on Electrical and Electronic Engineering, Statistical and Nonlinear Physics and Control and Systems Engineering. According to data from OpenAlex, Marcos Netto has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Electrical and Electronic Engineering, 9 papers in Statistical and Nonlinear Physics and 5 papers in Control and Systems Engineering. Recurrent topics in Marcos Netto's work include Power System Optimization and Stability (13 papers), Model Reduction and Neural Networks (9 papers) and Fluid Dynamics and Vibration Analysis (4 papers). Marcos Netto is often cited by papers focused on Power System Optimization and Stability (13 papers), Model Reduction and Neural Networks (9 papers) and Fluid Dynamics and Vibration Analysis (4 papers). Marcos Netto collaborates with scholars based in United States, Japan and China. Marcos Netto's co-authors include Lamine Mili, Junbo Zhao, Vladimir Terzija, Antonio Gómez‐Expósito, Ali Abur, A. P. Sakis Meliopoulos, Bikash C. Pal, Abhinav Kumar Singh, Innocent Kamwa and Junjian Qi and has published in prestigious journals such as IEEE Transactions on Power Systems, IEEE Access and Solar Energy.

In The Last Decade

Marcos Netto

18 papers receiving 1.3k citations

Hit Papers

Power System Dynamic State Estimation: Motivations, Defin... 2016 2026 2019 2022 2019 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcos Netto United States 12 1.0k 773 263 158 126 18 1.4k
Shaobu Wang United States 16 1.1k 1.1× 790 1.0× 205 0.8× 104 0.7× 97 0.8× 51 1.3k
Vassilis Kekatos United States 21 1.3k 1.2× 762 1.0× 242 0.9× 58 0.4× 283 2.2× 85 1.7k
M. Karrari Iran 21 1.2k 1.2× 1.1k 1.4× 159 0.6× 109 0.7× 201 1.6× 112 1.6k
B. Fardanesh United States 26 1.5k 1.5× 1.1k 1.5× 127 0.5× 35 0.2× 94 0.7× 88 1.9k
Dmitry Kosterev United States 23 2.2k 2.1× 1.4k 1.8× 156 0.6× 117 0.7× 58 0.5× 60 2.4k
Renke Huang United States 20 1.5k 1.5× 1.2k 1.5× 137 0.5× 52 0.3× 75 0.6× 96 1.8k
Ruisheng Diao United States 20 1.2k 1.2× 765 1.0× 141 0.5× 50 0.3× 73 0.6× 79 1.4k
Aleksandar Dimitrovski United States 18 947 0.9× 688 0.9× 115 0.4× 60 0.4× 235 1.9× 78 1.3k
J. Machowski Poland 14 2.5k 2.4× 1.8k 2.3× 86 0.3× 105 0.7× 141 1.1× 64 2.8k
N.G. Bretas Brazil 27 1.8k 1.8× 1.4k 1.8× 155 0.6× 147 0.9× 262 2.1× 171 2.2k

Countries citing papers authored by Marcos Netto

Since Specialization
Citations

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

Fields of papers citing papers by Marcos Netto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcos Netto

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

All Works

18 of 18 papers shown
1.
Xu, Yijun, Marcos Netto, & Lamine Mili. (2022). Propagating Parameter Uncertainty in Power System Nonlinear Dynamic Simulations Using a Koopman Operator-Based Surrogate Model. IEEE Transactions on Power Systems. 37(4). 3157–3160. 11 indexed citations
2.
Abolmasoumi, Amir Hossein, Marcos Netto, & Lamine Mili. (2022). Robust Dynamic Mode Decomposition. IEEE Access. 10. 65473–65484. 16 indexed citations
3.
Susuki, Yoshihiko, et al.. (2022). A mode-in-state contribution factor based on Koopman operator and its application to power system analysis. Nonlinear Theory and Its Applications IEICE. 13(2). 409–414. 1 indexed citations
4.
Tan, Bendong, Junbo Zhao, & Marcos Netto. (2022). A General Decentralized Dynamic State Estimation With Synchronous Generator Magnetic Saturation. IEEE Transactions on Power Systems. 38(1). 960–963. 5 indexed citations
5.
Tan, Bendong, Junbo Zhao, Marcos Netto, et al.. (2021). Power system inertia estimation: Review of methods and the impacts of converter-interfaced generations. International Journal of Electrical Power & Energy Systems. 134. 107362–107362. 146 indexed citations
6.
Netto, Marcos, et al.. (2021). On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers. 2021 IEEE Power & Energy Society General Meeting (PESGM). 1–5. 1 indexed citations
7.
Netto, Marcos, Yoshihiko Susuki, Venkat Krishnan, & Yingchen Zhang. (2021). On analytical construction of observable functions in extended dynamic mode decomposition for nonlinear estimation and prediction. 4190–4195. 16 indexed citations
8.
Zhao, Junbo, Marcos Netto, Zhenyu Huang, et al.. (2020). Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation. IEEE Transactions on Power Systems. 36(3). 2462–2472. 147 indexed citations
9.
Habte, Aron, et al.. (2020). Automated construction of clear-sky dictionary from all-sky imager data. Solar Energy. 212. 73–83. 7 indexed citations
10.
Netto, Marcos, et al.. (2020). Real-Time Modal Analysis of Electric Power Grids– The Need for Dynamic State Estimation. VTechWorks (Virginia Tech). 1–6. 3 indexed citations
11.
Netto, Marcos, Yoshihiko Susuki, Venkat Krishnan, & Yingchen Zhang. (2020). On Analytical Construction of Observable Functions in Extended Dynamic Mode Decomposition for Nonlinear Estimation and Prediction. IEEE Control Systems Letters. 5(6). 1868–1873. 16 indexed citations
12.
Zhao, Junbo, Junjian Qi, Zhenyu Huang, et al.. (2019). Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work. IEEE Transactions on Power Systems. 34(4). 3188–3198. 488 indexed citations breakdown →
13.
Netto, Marcos, Venkat Krishnan, Lamine Mili, Yoshihiko Susuki, & Yingchen Zhang. (2019). A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation. VTechWorks (Virginia Tech). 1–5. 5 indexed citations
14.
Netto, Marcos & Lamine Mili. (2018). A Robust Data-Driven Koopman Kalman Filter for Power Systems Dynamic State Estimation. IEEE Transactions on Power Systems. 33(6). 7228–7237. 86 indexed citations
15.
Netto, Marcos & Lamine Mili. (2018). Robust Koopman Operator-based Kalman Filter for Power Systems Dynamic State Estimation. 1–5. 15 indexed citations
16.
Netto, Marcos & Lamine Mili. (2017). A robust prony method for power system electromechanical modes identification. 1–5. 28 indexed citations
17.
Netto, Marcos & Lamine Mili. (2017). Robust Data Filtering for Estimating Electromechanical Modes of Oscillation via the Multichannel Prony Method. IEEE Transactions on Power Systems. 33(4). 4134–4143. 32 indexed citations
18.
Zhao, Junbo, Marcos Netto, & Lamine Mili. (2016). A Robust Iterated Extended Kalman Filter for Power System Dynamic State Estimation. IEEE Transactions on Power Systems. 32(4). 3205–3216. 350 indexed citations breakdown →

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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