Fernando Gama

1.9k total citations
44 papers, 927 citations indexed

About

Fernando Gama is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Electrical and Electronic Engineering. According to data from OpenAlex, Fernando Gama has authored 44 papers receiving a total of 927 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 11 papers in Statistical and Nonlinear Physics and 11 papers in Electrical and Electronic Engineering. Recurrent topics in Fernando Gama's work include Advanced Graph Neural Networks (24 papers), Complex Network Analysis Techniques (11 papers) and Advanced Memory and Neural Computing (7 papers). Fernando Gama is often cited by papers focused on Advanced Graph Neural Networks (24 papers), Complex Network Analysis Techniques (11 papers) and Advanced Memory and Neural Computing (7 papers). Fernando Gama collaborates with scholars based in United States, Netherlands and Spain. Fernando Gama's co-authors include Alejandro Ribeiro, Antonio G. Marqués, Geert Leus, Joan Bruna, Luana Ruiz, Amanda Prorok, Qingbiao Li, Elvin Isufi, Santiago Segarra and Zhan Gao and has published in prestigious journals such as IEEE Transactions on Signal Processing, Signal Processing and Energy and AI.

In The Last Decade

Fernando Gama

39 papers receiving 906 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fernando Gama United States	13	531	237	220	193	111	44	927
Rajgopal Kannan United States	17	493 0.9×	364 1.5×	529 2.4×	500 2.6×	62 0.6×	145	1.3k
Cheong Hee Park South Korea	18	392 0.7×	260 1.1×	69 0.3×	71 0.4×	55 0.5×	63	876
Junkai Ji China	20	742 1.4×	122 0.5×	171 0.8×	227 1.2×	46 0.4×	68	1.2k
Min Yao China	16	353 0.7×	211 0.9×	86 0.4×	190 1.0×	28 0.3×	104	973
Dragan Obradović Germany	17	270 0.5×	96 0.4×	248 1.1×	288 1.5×	84 0.8×	85	962
Ming Jin Australia	11	537 1.0×	125 0.5×	141 0.6×	59 0.3×	112 1.0×	35	864
Zhao Hai China	15	203 0.4×	80 0.3×	437 2.0×	355 1.8×	153 1.4×	162	1.0k
Richard Yi Da Xu Australia	18	293 0.6×	592 2.5×	108 0.5×	175 0.9×	49 0.4×	107	1.1k
Ruoyu Li China	11	441 0.8×	221 0.9×	127 0.6×	32 0.2×	73 0.7×	31	810
Xing Wang China	16	175 0.3×	80 0.3×	111 0.5×	185 1.0×	118 1.1×	75	777

Countries citing papers authored by Fernando Gama

Since Specialization

Citations

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

Fields of papers citing papers by Fernando Gama

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Gama

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Isufi, Elvin, Fernando Gama, David I Shuman, & Santiago Segarra. (2024). Graph Filters for Signal Processing and Machine Learning on Graphs. IEEE Transactions on Signal Processing. 72. 4745–4781. 37 indexed citations

Gama, Fernando, et al.. (2024). Unsupervised Optimal Power Flow Using Graph Neural Networks. 6885–6889. 11 indexed citations

Gama, Fernando, et al.. (2023). Unsupervised Learning of Sampling Distributions for Particle Filters. IEEE Transactions on Signal Processing. 71. 3852–3866. 8 indexed citations

Gama, Fernando, et al.. (2022). Distributed Optimal Control of Graph Symmetric Systems via Graph Filters. 2022 IEEE 61st Conference on Decision and Control (CDC). 50. 5245–5252. 1 indexed citations

Gama, Fernando & Somayeh Sojoudi. (2022). Distributed linear-quadratic control with graph neural networks. Signal Processing. 196. 108506–108506. 9 indexed citations

Gama, Fernando, et al.. (2021). A Robust Alternative for Graph Convolutional Neural Networks via Graph Neighborhood Filters. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 1573–1578. 5 indexed citations

Gama, Fernando, Elvin Isufi, Geert Leus, & Alejandro Ribeiro. (2020). Graphs, Convolutions, and Neural Networks.. arXiv (Cornell University). 5 indexed citations

Gama, Fernando & Somayeh Sojoudi. (2020). Graph Neural Networks for Decentralized Linear-Quadratic Control. arXiv (Cornell University). 1 indexed citations

Li, Qingbiao, Fernando Gama, Alejandro Ribeiro, & Amanda Prorok. (2020). Graph Neural Networks for Decentralized Path Planning. 1901–1903.

10.

Gama, Fernando, Elvin Isufi, Alejandro Ribeiro, & Geert Leus. (2019). Controllability of Bandlimited Graph Processes Over Random Time Varying Graphs. IEEE Transactions on Signal Processing. 67(24). 6440–6454. 16 indexed citations

11.

Gama, Fernando, Alejandro Ribeiro, & Joan Bruna. (2019). Stability of Graph Scattering Transforms. arXiv (Cornell University). 32. 8036–8046. 12 indexed citations

12.

Gama, Fernando, Antonio G. Marqués, Alejandro Ribeiro, & Geert Leus. (2019). Aggregation Graph Neural Networks. Research Repository (Delft University of Technology). 4943–4947. 7 indexed citations

13.

Gama, Fernando, Geert Leus, Antonio G. Marqués, & Alejandro Ribeiro. (2018). Convolutional Neural Networks via Node-Verying Graph Filters. Research Repository (Delft University of Technology). 12 indexed citations

14.

Gama, Fernando, Antonio G. Marqués, Geert Leus, & Alejandro Ribeiro. (2018). Convolutional Neural Network Architectures for Signals Supported on Graphs. IEEE Transactions on Signal Processing. 67(4). 1034–1049. 183 indexed citations

15.

Gama, Fernando, et al.. (2018). Predicting Power Outages Using Graph Neural Networks. 743–747. 46 indexed citations

16.

Gama, Fernando, Alejandro Ribeiro, & Joan Bruna. (2018). Diffusion Scattering Transforms on Graphs. arXiv (Cornell University). 10 indexed citations

17.

Gama, Fernando, Elvin Isufi, Geert Leus, & Alejandro Ribeiro. (2018). Control of Graph Signals Over Random Time-Varying Graphs. Research Repository (Delft University of Technology). 4169–4173. 4 indexed citations

18.

Gama, Fernando, Antonio G. Marqués, Gonzalo Mateos, & Alejandro Ribeiro. (2016). Rethinking sketching as sampling: Linear transforms of graph signals. 522–526. 7 indexed citations

19.

Gama, Fernando, et al.. (2016). VCloud. 193–198.

20.

Gama, Fernando, et al.. (2013). Drilling and Completing Cascade and Chinook Wells: A Design and Execution Case History. Offshore Technology Conference. 3 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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