Pavlos Protopapas

5.4k total citations
82 papers, 1.6k citations indexed

About

Pavlos Protopapas is a scholar working on Astronomy and Astrophysics, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Pavlos Protopapas has authored 82 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Astronomy and Astrophysics, 23 papers in Signal Processing and 21 papers in Artificial Intelligence. Recurrent topics in Pavlos Protopapas's work include Time Series Analysis and Forecasting (19 papers), Stellar, planetary, and galactic studies (18 papers) and Model Reduction and Neural Networks (13 papers). Pavlos Protopapas is often cited by papers focused on Time Series Analysis and Forecasting (19 papers), Stellar, planetary, and galactic studies (18 papers) and Model Reduction and Neural Networks (13 papers). Pavlos Protopapas collaborates with scholars based in United States, Chile and United Kingdom. Pavlos Protopapas's co-authors include N. A. D. Parlee, Hans Christian Andersen, David Sondak, Charles Alcock, Raúl Jiménez, Karim Pichara, Marios Mattheakis, Licia Verde, Dae Won Kim and P. A. Estévez and has published in prestigious journals such as Physical Review Letters, The Journal of Chemical Physics and The Astrophysical Journal.

In The Last Decade

Pavlos Protopapas

74 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pavlos Protopapas United States 21 533 325 314 257 234 82 1.6k
M. P. Hobson United Kingdom 20 688 1.3× 120 0.4× 19 0.1× 90 0.4× 112 0.5× 41 1.5k
R. J. Hanisch United States 19 1.0k 1.9× 108 0.3× 24 0.1× 136 0.5× 34 0.1× 105 1.7k
J. Vega Spain 21 179 0.3× 484 1.5× 242 0.8× 25 0.1× 66 0.3× 228 2.0k
E. A. Huerta United States 24 1.4k 2.5× 273 0.8× 30 0.1× 45 0.2× 110 0.5× 64 1.7k
M. Gelfusa Italy 19 118 0.2× 248 0.8× 110 0.4× 14 0.1× 105 0.4× 163 1.4k
Zarija Lukić United States 25 952 1.8× 144 0.4× 29 0.1× 37 0.1× 81 0.3× 93 1.9k
Gert Vegter Netherlands 22 154 0.3× 23 0.1× 80 0.3× 196 0.8× 374 1.6× 65 1.3k
David R. Andersen United States 28 1.4k 2.6× 93 0.3× 10 0.0× 72 0.3× 656 2.8× 144 3.0k
Aubrey B. Poore United States 19 90 0.2× 693 2.1× 56 0.2× 194 0.8× 385 1.6× 84 2.3k
H. J. Haubold Austria 17 199 0.4× 115 0.4× 26 0.1× 40 0.2× 902 3.9× 140 3.3k

Countries citing papers authored by Pavlos Protopapas

Since Specialization
Citations

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

Fields of papers citing papers by Pavlos Protopapas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavlos Protopapas

This figure shows the co-authorship network connecting the top 25 collaborators of Pavlos Protopapas. A scholar is included among the top collaborators of Pavlos Protopapas 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 Pavlos Protopapas. Pavlos Protopapas 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.
Jiménez, Raúl, et al.. (2025). Efficient PINNs via multi-head unimodular regularization of the solutions space. Communications Physics. 8(1).
2.
Jiménez, Raúl, et al.. (2024). Gravitational duals from equations of state. Journal of High Energy Physics. 2024(7). 7 indexed citations
3.
Mancoridis, Spiros, et al.. (2024). Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings. Proceedings of the ... Annual Hawaii International Conference on System Sciences.
4.
Protopapas, Pavlos, Cecilia Garraffo, Lindy Blackburn, et al.. (2023). Generating images of the M87* black hole using GANs. Monthly Notices of the Royal Astronomical Society. 527(4). 10965–10974. 3 indexed citations
5.
Katafygiotou, Martha, et al.. (2023). How Sustainable Design and Awareness May Affect the Real Estate Market. Sustainability. 15(23). 16425–16425. 2 indexed citations
6.
Landau, Susana J., et al.. (2023). Cosmology-informed neural networks to solve the background dynamics of the Universe. Physical review. D. 107(6). 8 indexed citations
7.
Yin, J., Daniel J. Eisenstein, Douglas P. Finkbeiner, & Pavlos Protopapas. (2022). A Conditional Autoencoder for Galaxy Photometric Parameter Estimation. Publications of the Astronomical Society of the Pacific. 134(1034). 44502–44502.
8.
Mattheakis, Marios, et al.. (2022). Physics-Informed Neural Networks for Quantum Eigenvalue Problems. 2022 International Joint Conference on Neural Networks (IJCNN). 1–8. 16 indexed citations
9.
10.
Sondak, David, et al.. (2020). Finding multiple solutions of odes with neural networks. Virtual Community of Pathological Anatomy (University of Castilla La Mancha). 2587. 1–7. 4 indexed citations
11.
Fang, Rui, David Sondak, Pavlos Protopapas, & Sauro Succi. (2019). Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow. Journal of Turbulence. 21(9-10). 525–543. 40 indexed citations
12.
Pichara, Karim, et al.. (2019). Streaming classification of variable stars. Monthly Notices of the Royal Astronomical Society. 492(2). 2897–2909. 11 indexed citations
13.
Gal, Kobi, et al.. (2018). Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems.. Educational Data Mining. 1 indexed citations
14.
Ishioka, Ryoko, M. J. Lehner, T. S. Axelrod, et al.. (2014). 台湾-アメリカの掩蔽調査プロジェクト恒星の変動性III 58の新変光星の検出. The Astronomical Journal. 147(4). 1–70. 3 indexed citations
15.
Kim, Dae‐Won, et al.. (2011). Automatic QSO Selection Algorithm Using Time Series Analysis and Machine Learning. 217. 1 indexed citations
16.
Protopapas, Pavlos, et al.. (2009). Discovering arbitrary event types in time series. Statistical Analysis and Data Mining The ASA Data Science Journal. 2(5-6). 396–411. 3 indexed citations
17.
Davé, Rajesh N., et al.. (2008). A Novel GUI Based Interactive Work Flow Application for Exploratory and Batch Processing of Light Curves. ASPC. 394. 357. 1 indexed citations
18.
Protopapas, Pavlos, J. Giammarco, L. Faccioli, et al.. (2006). Finding outlier light curves in catalogues of periodic variable stars. Monthly Notices of the Royal Astronomical Society. 369(2). 677–696. 52 indexed citations
19.
Diego, J. M., Pavlos Protopapas, H. B. Sandvik, & Max Tegmark. (2005). Non-parametric inversion of strong lensing systems. Monthly Notices of the Royal Astronomical Society. 360(2). 477–491. 59 indexed citations
20.
Protopapas, Pavlos, Abraham Klein, & Niels R. Walet. (1996). Application of a semimicroscopic core-particle coupling method to the backbending in odd deformed nuclei. Physical Review C. 54(2). 638–645. 4 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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