Travis E. Gibson

2.6k total citations · 1 hit paper
36 papers, 1.6k citations indexed

About

Travis E. Gibson is a scholar working on Control and Systems Engineering, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Travis E. Gibson has authored 36 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Control and Systems Engineering, 13 papers in Molecular Biology and 5 papers in Infectious Diseases. Recurrent topics in Travis E. Gibson's work include Gut microbiota and health (12 papers), Adaptive Control of Nonlinear Systems (11 papers) and Advanced Control Systems Optimization (8 papers). Travis E. Gibson is often cited by papers focused on Gut microbiota and health (12 papers), Adaptive Control of Nonlinear Systems (11 papers) and Advanced Control Systems Optimization (8 papers). Travis E. Gibson collaborates with scholars based in United States, Australia and China. Travis E. Gibson's co-authors include Anuradha M. Annaswamy, Eugene Lavretsky, Yang‐Yu Liu, Georg K. Gerber, Lynn Bry, Bryan B. Hsu, Pamela A. Silver, Amir Bashan, Qing Liu and Vladimir Yeliseyev and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Scientific Reports.

In The Last Decade

Travis E. Gibson

33 papers receiving 1.5k citations

Hit Papers

Dynamic Modulation of the Gut Microbiota and Metabolome b... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Travis E. Gibson United States 18 682 434 305 286 139 36 1.6k
Michihiro Kawanishi Japan 20 248 0.4× 316 0.7× 55 0.2× 83 0.3× 58 0.4× 122 1.4k
Marco Tulio Angulo Mexico 16 230 0.3× 452 1.0× 80 0.3× 48 0.2× 59 0.4× 37 943
Dimitar Dimitrov Bulgaria 28 121 0.2× 353 0.8× 381 1.2× 371 1.3× 256 1.8× 82 2.2k
E. Michael Gertz United States 18 1.5k 2.2× 95 0.2× 259 0.8× 140 0.5× 33 0.2× 42 2.7k
Joon‐Yong Lee South Korea 19 329 0.5× 53 0.1× 141 0.5× 208 0.7× 88 0.6× 88 1.2k
M.A. Jabbar Singapore 27 282 0.4× 410 0.9× 52 0.2× 204 0.7× 19 0.1× 108 1.9k
Chengmin Wang China 24 290 0.4× 154 0.4× 81 0.3× 540 1.9× 11 0.1× 125 2.1k
Toai Nguyen United States 19 713 1.0× 249 0.6× 165 0.5× 113 0.4× 15 0.1× 41 1.9k
Ibrahima N’Doye France 24 63 0.1× 456 1.1× 141 0.5× 253 0.9× 23 0.2× 127 2.0k
Jürgen P. Schulze United States 22 807 1.2× 43 0.1× 135 0.4× 301 1.1× 14 0.1× 109 2.4k

Countries citing papers authored by Travis E. Gibson

Since Specialization
Citations

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

Fields of papers citing papers by Travis E. Gibson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Travis E. Gibson. 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 Travis E. Gibson. The network helps show where Travis E. Gibson may publish in the future.

Co-authorship network of co-authors of Travis E. Gibson

This figure shows the co-authorship network connecting the top 25 collaborators of Travis E. Gibson. A scholar is included among the top collaborators of Travis E. Gibson 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 Travis E. Gibson. Travis E. Gibson 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.
Kim, Younhun, Colin J. Worby, Philippe Azimzadeh, et al.. (2025). Longitudinal profiling of low-abundance strains in microbiomes with ChronoStrain. Nature Microbiology. 10(5). 1184–1197.
2.
Gibson, Travis E., David E. Kaplan, Nicholas DiBenedetto, et al.. (2025). Learning ecosystem-scale dynamics from microbiome data with MDSINE2. Nature Microbiology. 10(10). 2550–2564. 1 indexed citations
3.
Moody, Thomas, Ravi U. Sheth, Miles Richardson, et al.. (2024). Spatiotemporal dynamics during niche remodeling by super-colonizing microbiota in the mammalian gut. Cell Systems. 15(11). 1002–1017.e4. 3 indexed citations
4.
Allegretti, Jessica R., et al.. (2022). Gut metabolites predict Clostridioides difficile recurrence. Microbiome. 10(1). 87–87. 30 indexed citations
5.
Ogata, Alana F., Adam M. Maley, Connie Wu, et al.. (2020). Ultra-Sensitive Serial Profiling of SARS-CoV-2 Antigens and Antibodies in Plasma to Understand Disease Progression in COVID-19 Patients with Severe Disease. Clinical Chemistry. 66(12). 1562–1572. 123 indexed citations
6.
Annaswamy, Anuradha M., et al.. (2020). A Class of High Order Tuners for Adaptive Systems. IEEE Control Systems Letters. 5(2). 391–396. 16 indexed citations
7.
Bashan, Amir, Travis E. Gibson, Jonathan Friedman, et al.. (2019). The universal dynamics of the human microbiome. Bulletin of the American Physical Society. 2019.
8.
Hsu, Bryan B., Travis E. Gibson, Vladimir Yeliseyev, et al.. (2019). Dynamic Modulation of the Gut Microbiota and Metabolome by Bacteriophages in a Mouse Model. Cell Host & Microbe. 25(6). 803–814.e5. 369 indexed citations breakdown →
9.
Gibson, Travis E., et al.. (2019). Accelerated Learning in the Presence of Time Varying Features with Applications to Machine Learning and Adaptive Control..
10.
Gibson, Travis E. & Georg K. Gerber. (2018). Robust and Scalable Models of Microbiome Dynamics. International Conference on Machine Learning. 1763–1772. 2 indexed citations
11.
McGeachie, Michael J., Joanne E. Sordillo, Travis E. Gibson, et al.. (2016). Longitudinal Prediction of the Infant Gut Microbiome with Dynamic Bayesian Networks. Scientific Reports. 6(1). 20359–20359. 49 indexed citations
12.
Gibson, Travis E.. (2016). Adaptation and synchronization over a network: Asymptotic error convergence and pinning. 2969–2974. 12 indexed citations
13.
Bashan, Amir, Travis E. Gibson, Jonathan Friedman, et al.. (2016). Universality of human microbial dynamics. Nature. 534(7606). 259–262. 183 indexed citations
14.
Gibson, Travis E., et al.. (2016). Inferring human microbial dynamics from temporal metagenomics data: Pitfalls and lessons. BioEssays. 39(2). 50 indexed citations
15.
Gibson, Travis E., et al.. (2016). On the Origins and Control of Community Types in the Human Microbiome. PLoS Computational Biology. 12(2). e1004688–e1004688. 53 indexed citations
16.
Gibson, Travis E., Anuradha M. Annaswamy, & Eugene Lavretsky. (2013). Adaptive Systems with Closed–loop Reference Models: Composite control and observer feedback. IFAC Proceedings Volumes. 46(11). 440–445. 10 indexed citations
17.
Annaswamy, Anuradha M., Eugene Lavretsky, Zachary T. Dydek, Travis E. Gibson, & Megumi Matsutani. (2012). Recent results in robust adaptive flight control systems. International Journal of Adaptive Control and Signal Processing. 27(1-2). 4–21. 26 indexed citations
18.
Gibson, Travis E., Luis G. Crespo, & Anuradha M. Annaswamy. (2009). Adaptive control of hypersonic vehicles in the presence of modeling uncertainties. 3178–3183. 74 indexed citations
19.
Crespo, Luis G., Megumi Matsutani, Jinho Jang, Travis E. Gibson, & Anuradha M. Annaswamy. (2009). Design and Verification of an Adaptive Controller for the Generic Transport Model. AIAA Guidance, Navigation, and Control Conference. 23 indexed citations
20.
Buchanan, Andrew, et al.. (2006). Fifteen years of performance-based design in New Zealand. University of Canterbury Research Repository (University of Canterbury). 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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