Francis J. Alexander

2.8k total citations
69 papers, 1.9k citations indexed

About

Francis J. Alexander is a scholar working on Condensed Matter Physics, Statistical and Nonlinear Physics and Computational Mechanics. According to data from OpenAlex, Francis J. Alexander has authored 69 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Condensed Matter Physics, 14 papers in Statistical and Nonlinear Physics and 14 papers in Computational Mechanics. Recurrent topics in Francis J. Alexander's work include Theoretical and Computational Physics (20 papers), Lattice Boltzmann Simulation Studies (10 papers) and Fluid Dynamics and Turbulent Flows (9 papers). Francis J. Alexander is often cited by papers focused on Theoretical and Computational Physics (20 papers), Lattice Boltzmann Simulation Studies (10 papers) and Fluid Dynamics and Turbulent Flows (9 papers). Francis J. Alexander collaborates with scholars based in United States, Netherlands and Canada. Francis J. Alexander's co-authors include Alejandro L. Garcia, Shiyi Chen, Berni J. Alder, James D. Sterling, Turab Lookman, Gregory L. Eyink, Krishna Rajan, Daryl Grunau, Juan M. Restrepo and Joel L. Lebowitz and has published in prestigious journals such as Physical Review Letters, SHILAP Revista de lepidopterología and Physical review. B, Condensed matter.

In The Last Decade

Francis J. Alexander

68 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francis J. Alexander United States 22 866 432 391 289 268 69 1.9k
Pingwen Zhang China 32 1.1k 1.3× 670 1.6× 385 1.0× 475 1.6× 253 0.9× 155 3.1k
Darren Crowdy United Kingdom 28 1.4k 1.6× 172 0.4× 370 0.9× 211 0.7× 488 1.8× 179 2.8k
Andreas Prohl Germany 24 1.2k 1.4× 523 1.2× 238 0.6× 220 0.8× 106 0.4× 88 2.0k
Rodolfo R. Rosales United States 24 727 0.8× 116 0.3× 263 0.7× 88 0.3× 166 0.6× 64 1.8k
Augusto Visintin Italy 24 599 0.7× 651 1.5× 424 1.1× 141 0.5× 92 0.3× 98 2.7k
Alejandro L. Garcia United States 32 1.9k 2.2× 463 1.1× 1.6k 4.0× 394 1.4× 209 0.8× 103 3.6k
Albert Fannjiang United States 21 490 0.6× 192 0.4× 119 0.3× 157 0.5× 73 0.3× 82 1.6k
Xiantao Li United States 20 480 0.6× 446 1.0× 129 0.3× 180 0.6× 119 0.4× 92 1.7k
Zhonghua Qiao Hong Kong 27 1.5k 1.7× 1.4k 3.1× 190 0.5× 182 0.6× 80 0.3× 89 2.5k
Giovanni Samaey Belgium 21 366 0.4× 293 0.7× 114 0.3× 176 0.6× 60 0.2× 110 1.6k

Countries citing papers authored by Francis J. Alexander

Since Specialization
Citations

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

Fields of papers citing papers by Francis J. Alexander

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francis J. Alexander. 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 Francis J. Alexander. The network helps show where Francis J. Alexander may publish in the future.

Co-authorship network of co-authors of Francis J. Alexander

This figure shows the co-authorship network connecting the top 25 collaborators of Francis J. Alexander. A scholar is included among the top collaborators of Francis J. Alexander 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 Francis J. Alexander. Francis J. Alexander 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.
Urban, Nathan M., et al.. (2024). Multi-objective latent space optimization of generative molecular design models. Patterns. 5(10). 101042–101042. 12 indexed citations
2.
Pouchard, Line, Kristofer G. Reyes, Francis J. Alexander, & Byung-Jun Yoon. (2023). A rigorous uncertainty-aware quantification framework is essential for reproducible and replicable machine learning workflows. Digital Discovery. 2(5). 1251–1258. 5 indexed citations
3.
4.
Qian, Xiaoning, Li Lynn Tan, Shantenu Jha, et al.. (2023). Optimal decision-making in high-throughput virtual screening pipelines. Patterns. 4(11). 100875–100875. 5 indexed citations
5.
Qian, Xiaoning, et al.. (2022). Synthetic data for design and evaluation of binary classifiers in the context of Bayesian transfer learning. Data in Brief. 42. 108113–108113. 1 indexed citations
6.
Zhao, Guang, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, & Xiaoning Qian. (2021). Efficient Active Learning for Gaussian Process Classification by Error Reduction. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 8 indexed citations
7.
Dougherty, Edward R., et al.. (2021). Uncertainty-aware Active Learning for Optimal Bayesian Classifier. 7 indexed citations
8.
Dougherty, Edward R., Lori A. Dalton, & Francis J. Alexander. (2015). Small data is the problem. 418–422. 2 indexed citations
9.
Haut, Terry, et al.. (2015). Physics-based statistical learning approach to mesoscopic model selection. Physical Review E. 92(5). 53301–53301. 5 indexed citations
10.
Alexander, Francis J., et al.. (2014). Noise propagation in hybrid models of nonlinear systems: The Ginzburg–Landau equation. Journal of Computational Physics. 262. 313–324. 9 indexed citations
11.
Alexander, Francis J. & Philip Rosenau. (2010). Quasicontinuum Fokker-Planck equation. Physical Review E. 81(4). 41902–41902. 2 indexed citations
12.
Alexander, Francis J., Gregory Johnson, Gregory L. Eyink, & Ioannis G. Kevrekidis. (2008). Equation-free implementation of statistical moment closures. Physical Review E. 77(2). 26701–26701. 8 indexed citations
13.
Teuscher, Christof, Ilya Nemenman, & Francis J. Alexander. (2008). Novel computing paradigms: Quo vadis?. Physica D Nonlinear Phenomena. 237(9). v–viii. 2 indexed citations
14.
Eyink, Gregory L., Juan M. Restrepo, & Francis J. Alexander. (2004). A mean field approximation in data assimilation for nonlinear dynamics. Physica D Nonlinear Phenomena. 195(3-4). 347–368. 28 indexed citations
15.
Alexander, Francis J., Bruce M. Boghosian, Richard C. Brower, & S. Roy Kimura. (2001). Fourier acceleration of Langevin molecular dynamics. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 64(6). 66704–66704. 4 indexed citations
16.
Alexander, Francis J. & Alejandro L. Garcia. (1997). The Direct Simulation Monte Carlo Method. Computers in Physics. 11(6). 588–593. 151 indexed citations
17.
Boghosian, Bruce M., Francis J. Alexander, & Peter V. Coveney. (1997). Guest Editors' Preface: Discrete Models of Complex Fluid Dynamics. International Journal of Modern Physics C. 8(4). 637–640. 5 indexed citations
18.
Garcia, Alejandro L., Francis J. Alexander, & Berni J. Alder. (1997). A particle method with adjustable transport properties—the generalized consistent Boltzmann algorithm. Journal of Statistical Physics. 89(1-2). 403–409. 11 indexed citations
19.
Tamayo, Pablo, Rajan Gupta, & Francis J. Alexander. (1996). TWO-TEMPERATURE NON-EQUILIBRIUM ISING MODELS. International Journal of Modern Physics C. 7(3). 389–399. 2 indexed citations
20.
Wu, Yanan, Francis J. Alexander, Turab Lookman, & Shiyi Chen. (1995). Effects of Hydrodynamics on Phase Transition Kinetics in Two-Dimensional Binary Fluids. Physical Review Letters. 74(19). 3852–3855. 46 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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