Brian M. de Silva

15 total papers · 533 total citations
6 papers, 257 citations indexed

About

Brian M. de Silva is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics and Control and Systems Engineering. According to data from OpenAlex, Brian M. de Silva has authored 6 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Statistical and Nonlinear Physics and 2 papers in Control and Systems Engineering. Recurrent topics in Brian M. de Silva's work include Model Reduction and Neural Networks (3 papers), Probabilistic and Robust Engineering Design (2 papers) and Anomaly Detection Techniques and Applications (2 papers). Brian M. de Silva is often cited by papers focused on Model Reduction and Neural Networks (3 papers), Probabilistic and Robust Engineering Design (2 papers) and Anomaly Detection Techniques and Applications (2 papers). Brian M. de Silva collaborates with scholars based in United States and France. Brian M. de Silva's co-authors include J. Nathan Kutz, Steven L. Brunton, Kathleen Champion, Jean-Christophe Loiseau, Markus Quade, Jared Callaham, Charles B. Delahunt, Zachary G. Nicolaou, Urban Fasel and Kadierdan Kaheman and has published in prestigious journals such as AIAA Journal, The Journal of Open Source Software and Applied Mathematics.

In The Last Decade

Brian M. de Silva

6 papers receiving 249 citations

Hit Papers

PySINDy: A comprehensive ... 2022 2026 2023 2024 2022 25 50 75 100

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Brian M. de Silva 153 77 64 53 41 6 257
Kadierdan Kaheman 202 1.3× 103 1.3× 88 1.4× 71 1.3× 43 1.0× 6 322
Kathleen Champion 217 1.4× 95 1.2× 82 1.3× 75 1.4× 51 1.2× 4 331
Markus Quade 124 0.8× 57 0.7× 85 1.3× 55 1.0× 27 0.7× 8 243
Levi D. McClenny 179 1.2× 35 0.5× 58 0.9× 27 0.5× 63 1.5× 7 324
Travis Askham 150 1.0× 60 0.8× 48 0.8× 53 1.0× 87 2.1× 13 291
Zheyuan Hu 187 1.2× 35 0.5× 72 1.1× 29 0.5× 66 1.6× 15 300
Pengzhan Jin 192 1.3× 33 0.4× 101 1.6× 23 0.4× 49 1.2× 9 278
Yaohua Zang 186 1.2× 20 0.3× 43 0.7× 45 0.8× 81 2.0× 6 251
J. Nathan Kutz 106 0.7× 70 0.9× 67 1.0× 25 0.5× 56 1.4× 2 331
Carl Leake 122 0.8× 31 0.4× 42 0.7× 26 0.5× 51 1.2× 14 251

Countries citing papers authored by Brian M. de Silva

Since Specialization
Citations

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

Fields of papers citing papers by Brian M. de Silva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian M. de Silva. 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 Brian M. de Silva. The network helps show where Brian M. de Silva may publish in the future.

Co-authorship network of co-authors of Brian M. de Silva

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

All Works

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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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