Antonios Zagaris

745 total citations
19 papers, 505 citations indexed

About

Antonios Zagaris is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Computer Networks and Communications. According to data from OpenAlex, Antonios Zagaris has authored 19 papers receiving a total of 505 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistical and Nonlinear Physics, 6 papers in Computational Mechanics and 5 papers in Computer Networks and Communications. Recurrent topics in Antonios Zagaris's work include stochastic dynamics and bifurcation (5 papers), Nonlinear Dynamics and Pattern Formation (5 papers) and Advanced Thermodynamics and Statistical Mechanics (4 papers). Antonios Zagaris is often cited by papers focused on stochastic dynamics and bifurcation (5 papers), Nonlinear Dynamics and Pattern Formation (5 papers) and Advanced Thermodynamics and Statistical Mechanics (4 papers). Antonios Zagaris collaborates with scholars based in Netherlands, United States and France. Antonios Zagaris's co-authors include Tasso J. Kaper, Hans G. Kaper, C. W. Gear, Ioannis G. Kevrekidis, Adrian Muntean, Jens D. M. Rademacher, Yannis Kevrekidis, Arjen Doelman, Hans V. Westerhoff and Mahdi Kooshkbaghi and has published in prestigious journals such as Journal of Computational Physics, FEBS Journal and Physica D Nonlinear Phenomena.

In The Last Decade

Antonios Zagaris

19 papers receiving 465 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Antonios Zagaris Netherlands 11 196 165 117 110 74 19 505
William F. Langford Canada 17 481 2.5× 190 1.2× 508 4.3× 77 0.7× 19 0.3× 34 1.0k
Kurt Lust Belgium 11 152 0.8× 156 0.9× 83 0.7× 18 0.2× 11 0.1× 22 406
Jean Maquet France 14 348 1.8× 61 0.4× 268 2.3× 76 0.7× 34 0.5× 29 651
P. A. Lagerstrom United States 12 192 1.0× 190 1.2× 118 1.0× 31 0.3× 22 0.3× 23 675
Stephen Schecter United States 17 254 1.3× 165 1.0× 220 1.9× 19 0.2× 9 0.1× 73 834
Thomas Wanner United States 18 109 0.6× 138 0.8× 51 0.4× 15 0.1× 28 0.4× 59 817
M. Gorman United States 20 242 1.2× 498 3.0× 411 3.5× 50 0.5× 130 1.8× 34 871
Francesco Gargano Italy 12 137 0.7× 95 0.6× 27 0.2× 34 0.3× 7 0.1× 51 418
Manuel Carretero Spain 11 104 0.5× 93 0.6× 35 0.3× 47 0.4× 5 0.1× 31 389
Evelyn Sander United States 15 257 1.3× 28 0.2× 130 1.1× 21 0.2× 9 0.1× 44 452

Countries citing papers authored by Antonios Zagaris

Since Specialization
Citations

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

Fields of papers citing papers by Antonios Zagaris

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Antonios Zagaris

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

All Works

19 of 19 papers shown
1.
Kooshkbaghi, Mahdi, et al.. (2019). Manifold learning for parameter reduction. Journal of Computational Physics. 392. 419–431. 30 indexed citations
2.
Mathijssen, Simon G. J., M. Bozkurt, Antonios Zagaris, et al.. (2019). Color mixing in overlay metrology for greater accuracy and robustness. 10585. 50–50. 6 indexed citations
3.
Swart, Huib E. de, et al.. (2018). Sensitivity of tidal characteristics in double inlet systems to momentum dissipation on tidal flats: a perturbation analysis. Ocean Dynamics. 68(4-5). 439–455. 8 indexed citations
4.
Muntean, Adrian, Jens D. M. Rademacher, & Antonios Zagaris. (2016). Macroscopic and Large Scale Phenomena: Coarse Graining, Mean Field Limits and Ergodicity. CERN Document Server (European Organization for Nuclear Research). 27 indexed citations
5.
Kaper, Hans G., Tasso J. Kaper, & Antonios Zagaris. (2015). Geometry of the Computational Singular Perturbation Method. Mathematical Modelling of Natural Phenomena. 10(3). 16–30. 17 indexed citations
6.
Doelman, Arjen, et al.. (2015). The effect of slow spatial processes on emerging spatiotemporal patterns. Chaos An Interdisciplinary Journal of Nonlinear Science. 25(3). 36408–36408. 2 indexed citations
7.
Doelman, Arjen, et al.. (2015). Tracking pattern evolution through extended center manifold reduction and singular perturbations. Physica D Nonlinear Phenomena. 298-299. 48–67. 6 indexed citations
8.
Meijer, Lenny H. H., André Estevez‐Torres, Yannick Rondelez, et al.. (2014). Automated Design of Programmable Enzyme-Driven DNA Circuits. ACS Synthetic Biology. 4(6). 735–745. 19 indexed citations
9.
Zagaris, Antonios, et al.. (2012). Stability and stabilization of the constrained runs schemes for equation-free projection to a slow manifold. Discrete and Continuous Dynamical Systems. 32(8). 2759–2803. 8 indexed citations
10.
Zagaris, Antonios, et al.. (2009). Simplified yet highly accurate enzyme kinetics for cases of low substrate concentrations. FEBS Journal. 276(19). 5491–5506. 20 indexed citations
11.
Zagaris, Antonios, C. W. Gear, Tasso J. Kaper, & Yannis Kevrekidis. (2009). Analysis of the accuracy and convergence of equation-free projection to a slow manifold. ESAIM Mathematical Modelling and Numerical Analysis. 43(4). 757–784. 29 indexed citations
12.
Zagaris, Antonios, et al.. (2009). Blooming in a Nonlocal, Coupled Phytoplankton-Nutrient Model. SIAM Journal on Applied Mathematics. 69(4). 1174–1204. 15 indexed citations
13.
Kalachev, Leonid, et al.. (2007). Reduction for Michaelis-Menten-Henri kinetics in the presence of diffusion. Electronic Journal of Differential Equations. 2007. 155–184. 4 indexed citations
14.
Zagaris, Antonios, et al.. (2007). Blooming in a non-local, coupled phytoplankton–nutrient model. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–27. 1 indexed citations
15.
Zagaris, Antonios, Hans G. Kaper, & Tasso J. Kaper. (2005). Two perspectives on reduction of ordinary differential equations. Mathematische Nachrichten. 278(12-13). 1629–1642. 29 indexed citations
16.
Gear, C. W., Tasso J. Kaper, Ioannis G. Kevrekidis, & Antonios Zagaris. (2005). Projecting to a Slow Manifold: Singularly Perturbed Systems and Legacy Codes. SIAM Journal on Applied Dynamical Systems. 4(3). 711–732. 101 indexed citations
17.
Zagaris, Antonios. (2005). ANALYSIS OF REDUCTION METHODS FOR MULTISCALE PROBLEMS. 1 indexed citations
18.
Zagaris, Antonios, Hans G. Kaper, & Tasso J. Kaper. (2004). Analysis of the Computational Singular Perturbation Reduction Method forChemical Kinetics. Journal of Nonlinear Science. 14(1). 59–91. 111 indexed citations
19.
Zagaris, Antonios, Hans G. Kaper, & Tasso J. Kaper. (2004). Fast and Slow Dynamics for the Computational Singular Perturbation Method. Multiscale Modeling and Simulation. 2(4). 613–638. 71 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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