Eric Forgoston

580 total citations
41 papers, 391 citations indexed

About

Eric Forgoston is a scholar working on Statistical and Nonlinear Physics, Computational Mechanics and Molecular Biology. According to data from OpenAlex, Eric Forgoston has authored 41 papers receiving a total of 391 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistical and Nonlinear Physics, 9 papers in Computational Mechanics and 8 papers in Molecular Biology. Recurrent topics in Eric Forgoston's work include Fluid Dynamics and Turbulent Flows (8 papers), Evolution and Genetic Dynamics (7 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (7 papers). Eric Forgoston is often cited by papers focused on Fluid Dynamics and Turbulent Flows (8 papers), Evolution and Genetic Dynamics (7 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (7 papers). Eric Forgoston collaborates with scholars based in United States, United Kingdom and Netherlands. Eric Forgoston's co-authors include Ira B. Schwartz, Anatoli Tumin, M. Ani Hsieh, Lora Billings, Simone Bianco, Luis Mier-y-Terán-Romero, Leah B. Shaw, James H. Kaufman, Jennifer Adams Krumins and Valdis Krumins and has published in prestigious journals such as PLoS ONE, Biomass and Bioenergy and Physics of Fluids.

In The Last Decade

Eric Forgoston

40 papers receiving 373 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Forgoston United States 12 109 88 68 49 47 41 391
Toshiyuki OGAWA Japan 14 136 1.2× 141 1.6× 59 0.9× 82 1.7× 57 1.2× 134 718
V. Panferov United States 9 124 1.1× 118 1.3× 119 1.8× 47 1.0× 90 1.9× 13 502
Vladimir Sobolev Russia 16 222 2.0× 288 3.3× 131 1.9× 93 1.9× 39 0.8× 92 797
Tsuyoshi Mizuguchi Japan 8 175 1.6× 57 0.6× 29 0.4× 29 0.6× 7 0.1× 27 385
Richard Rebarber United States 20 142 1.3× 98 1.1× 29 0.4× 105 2.1× 38 0.8× 67 1.3k
Razvan C. Fetecau Canada 13 122 1.1× 131 1.5× 125 1.8× 120 2.4× 243 5.2× 42 669
Francesco Gargano Italy 12 27 0.2× 137 1.6× 95 1.4× 37 0.8× 57 1.2× 51 418
Hamid Ait Abderrahmane United Arab Emirates 14 43 0.4× 29 0.3× 242 3.6× 67 1.4× 17 0.4× 56 516
Louis F. Rossi United States 12 50 0.5× 47 0.5× 193 2.8× 10 0.2× 9 0.2× 35 478
Carlos Escudero Spain 13 102 0.9× 181 2.1× 16 0.2× 72 1.5× 84 1.8× 40 627

Countries citing papers authored by Eric Forgoston

Since Specialization
Citations

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

Fields of papers citing papers by Eric Forgoston

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Forgoston

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Forgoston. A scholar is included among the top collaborators of Eric Forgoston 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 Eric Forgoston. Eric Forgoston 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.
Thorne, Michael A. S., et al.. (2025). Exploring the dynamics of Lotka–Volterra systems: Efficiency, extinction order, and predictive machine learning. Chaos An Interdisciplinary Journal of Nonlinear Science. 35(3). 1 indexed citations
2.
Forgoston, Eric, et al.. (2022). Characterizing outbreak vulnerability in a stochastic SIS model with an external disease reservoir. Journal of The Royal Society Interface. 19(192). 20220253–20220253. 1 indexed citations
3.
Karr, Jonathan R., Rahuman S. Malik‐Sheriff, James M. Osborne, et al.. (2022). Model Integration in Computational Biology: The Role of Reproducibility, Credibility and Utility. PubMed. 2. 9 indexed citations
4.
Forgoston, Eric, et al.. (2022). Controlling epidemic extinction using early warning signals. International Journal of Dynamics and Control. 11(2). 851–861. 3 indexed citations
5.
Thorne, Michael A. S., Eric Forgoston, Lora Billings, & Anje‐Margriet Neutel. (2021). Matrix Scaling and Tipping Points. SIAM Journal on Applied Dynamical Systems. 20(2). 1090–1103. 2 indexed citations
6.
Forgoston, Eric, et al.. (2020). Bridging the gap: Machine learning to resolve improperly modeled dynamics. Physica D Nonlinear Phenomena. 414. 132736–132736. 7 indexed citations
7.
Forgoston, Eric, et al.. (2019). Using control to shape stochastic escape and switching dynamics. Chaos An Interdisciplinary Journal of Nonlinear Science. 29(5). 53128–53128. 5 indexed citations
8.
Billings, Lora & Eric Forgoston. (2017). Seasonal forcing in stochastic epidemiology models. Ricerche di Matematica. 67(1). 27–47. 14 indexed citations
9.
Krumins, Jennifer Adams, Valdis Krumins, Eric Forgoston, Lora Billings, & Wim H. van der Putten. (2015). Herbivory and Stoichiometric Feedbacks to Primary Production. PLoS ONE. 10(6). e0129775–e0129775. 14 indexed citations
10.
Forgoston, Eric, Leah B. Shaw, & Ira B. Schwartz. (2015). A Framework for Inferring Unobserved Multistrain Epidemic Subpopulations Using Synchronization Dynamics. Bulletin of Mathematical Biology. 77(7). 1437–1455. 1 indexed citations
11.
Billings, Lora, et al.. (2014). Analysis and Control of Pre-extinction Dynamics in Stochastic Populations. Bulletin of Mathematical Biology. 76(12). 3122–3137. 6 indexed citations
12.
Hsieh, M. Ani, et al.. (2014). Experimental validation of robotic manifold tracking in gyre-like flows. 2306–2311. 4 indexed citations
13.
Hsieh, M. Ani, et al.. (2014). Robotic Tracking of Coherent Structures in Flows. IEEE Transactions on Robotics. 30(3). 593–603. 38 indexed citations
14.
Forgoston, Eric & Ira B. Schwartz. (2013). Predicting Unobserved Exposures from Seasonal Epidemic Data. Bulletin of Mathematical Biology. 75(9). 1450–1471. 6 indexed citations
15.
Mier-y-Terán-Romero, Luis, Eric Forgoston, & Ira B. Schwartz. (2012). Coherent Pattern Prediction in Swarms of Delay-Coupled Agents. IEEE Transactions on Robotics. 28(5). 1034–1044. 25 indexed citations
16.
Mier-y-Terán-Romero, Luis, Eric Forgoston, & Ira B. Schwartz. (2011). Noise, bifurcations, and modeling of interacting particle systems. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. 3905–3910. 11 indexed citations
17.
Forgoston, Eric, Simone Bianco, Leah B. Shaw, & Ira B. Schwartz. (2010). Maximal Sensitive Dependence and the Optimal Path to Epidemic Extinction. Bulletin of Mathematical Biology. 73(3). 495–514. 19 indexed citations
18.
Forgoston, Eric & Ira B. Schwartz. (2008). Delay-induced instabilities in self-propelling swarms. Physical Review E. 77(3). 35203–35203. 37 indexed citations
19.
Forgoston, Eric & Anatoli Tumin. (2005). Three-dimensional Wave Packet in a Hypersonic Boundary Layer. 43rd AIAA Aerospace Sciences Meeting and Exhibit. 5 indexed citations
20.
Forgoston, Eric, Anatoli Tumin, & David E. Ashpis. (2005). Distributed Blowing and Suction for the Purpose of Streak Control in a Boundary Layer Subjected to a Favorable Pressure Gradient. NASA STI Repository (National Aeronautics and Space Administration). 1 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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