Eric Klavins

5.0k total citations · 1 hit paper
80 papers, 3.2k citations indexed

About

Eric Klavins is a scholar working on Molecular Biology, Mechanical Engineering and Computer Networks and Communications. According to data from OpenAlex, Eric Klavins has authored 80 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 21 papers in Mechanical Engineering and 16 papers in Computer Networks and Communications. Recurrent topics in Eric Klavins's work include Modular Robots and Swarm Intelligence (21 papers), Gene Regulatory Network Analysis (20 papers) and Formal Methods in Verification (11 papers). Eric Klavins is often cited by papers focused on Modular Robots and Swarm Intelligence (21 papers), Gene Regulatory Network Analysis (20 papers) and Formal Methods in Verification (11 papers). Eric Klavins collaborates with scholars based in United States, Latvia and United Kingdom. Eric Klavins's co-authors include Mark Yim, Behnam Salemi, Mark Moll, Hod Lipson, Gregory S. Chirikjian, Daniela Rus, Wei‐Min Shen, Jennifer L. Nemhauser, Nils Napp and Robert G. Egbert and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Eric Klavins

78 papers receiving 3.1k citations

Hit Papers

Modular Self-Reconfigurable Robot Systems [Grand Challeng... 2007 2026 2013 2019 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Klavins United States 28 1.3k 1.2k 581 575 492 80 3.2k
Mark Moll United States 25 613 0.5× 1.3k 1.1× 756 1.3× 413 0.7× 509 1.0× 84 3.9k
Vito Trianni Italy 31 126 0.1× 1.3k 1.1× 245 0.4× 1.3k 2.3× 232 0.5× 85 2.7k
Chien‐Hung Liu Taiwan 31 476 0.4× 747 0.6× 712 1.2× 160 0.3× 35 0.1× 177 3.5k
Eliseo Ferrante Netherlands 19 168 0.1× 1.1k 0.9× 257 0.4× 1.3k 2.2× 284 0.6× 66 2.5k
Andy M. Tyrrell United Kingdom 23 487 0.4× 342 0.3× 312 0.5× 213 0.4× 36 0.1× 215 2.1k
Michael Rubenstein United States 22 147 0.1× 1.4k 1.2× 555 1.0× 824 1.4× 690 1.4× 55 2.3k
Peter Will United States 29 208 0.2× 1.5k 1.3× 825 1.4× 506 0.9× 628 1.3× 89 2.7k
Spring Berman United States 20 150 0.1× 585 0.5× 380 0.7× 573 1.0× 171 0.3× 76 1.4k
Kasper Støy Denmark 20 87 0.1× 1.1k 0.9× 419 0.7× 471 0.8× 362 0.7× 85 1.6k
Jacob Beal United States 27 1.6k 1.3× 659 0.6× 246 0.4× 714 1.2× 14 0.0× 147 2.7k

Countries citing papers authored by Eric Klavins

Since Specialization
Citations

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

Fields of papers citing papers by Eric Klavins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Klavins

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Klavins. A scholar is included among the top collaborators of Eric Klavins 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 Klavins. Eric Klavins 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.
Lange, Orlando de, et al.. (2023). Open-source workflow design and management software to interrogate duckweed growth conditions and stress responses. Plant Methods. 19(1). 95–95. 1 indexed citations
2.
Vrana, Justin D., Nuttada Panpradist, Daisy Ko, et al.. (2022). Implementation of an interactive mobile application to pilot a rapid assay to detect HIV drug resistance mutations in Kenya. SHILAP Revista de lepidopterología. 2(2). e0000185–e0000185. 3 indexed citations
3.
Maguire, Jack B., Hugh K. Haddox, Devin Strickland, et al.. (2020). Perturbing the energy landscape for improved packing during computational protein design. Proteins Structure Function and Bioinformatics. 89(4). 436–449. 87 indexed citations
4.
Hossain, Ayaan, et al.. (2020). Automated design of thousands of nonrepetitive parts for engineering stable genetic systems. Nature Biotechnology. 38(12). 1466–1475. 94 indexed citations
5.
Khakhar, Arjun, et al.. (2018). Synthetic hormone-responsive transcription factors can monitor and re-program plant development. eLife. 7. 85 indexed citations
6.
Berger, S. A., et al.. (2017). High-throughput characterization of protein–protein interactions by reprogramming yeast mating. Proceedings of the National Academy of Sciences. 114(46). 12166–12171. 57 indexed citations
7.
Klavins, Eric. (2017). Aquarium: Toward Reproducible Molecular Biology. Figshare. 1 indexed citations
8.
Lange, Orlando de, Eric Klavins, & Jennifer L. Nemhauser. (2017). Synthetic genetic circuits in crop plants. Current Opinion in Biotechnology. 49. 16–22. 34 indexed citations
9.
Gander, Miles, et al.. (2017). Digital logic circuits in yeast with CRISPR-dCas9 NOR gates. Nature Communications. 8(1). 15459–15459. 154 indexed citations
10.
Guseman, Jessica M., Antje Hellmuth, Amy Lanctot, et al.. (2015). Auxin-induced degradation dynamics set the pace for lateral root development. Journal of Cell Science. 128(6). e1–e1. 23 indexed citations
11.
Miller, Aaron W., et al.. (2014). A Low Cost, Customizable Turbidostat for Use in Synthetic Circuit Characterization. ACS Synthetic Biology. 4(1). 32–38. 85 indexed citations
12.
Klavins, Eric, et al.. (2014). Framework for Engineering Finite State Machines in Gene Regulatory Networks. ACS Synthetic Biology. 3(9). 652–665. 19 indexed citations
13.
Thorsley, David & Eric Klavins. (2012). Estimation and Discrimination of Stochastic Biochemical Circuits from Time-Lapse Microscopy Data. PLoS ONE. 7(11). e47151–e47151. 4 indexed citations
14.
Yim, Mark, Wei‐Min Shen, Behnam Salemi, et al.. (2007). Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics]. IEEE Robotics & Automation Magazine. 14(1). 43–52. 712 indexed citations breakdown →
15.
Yim, Mark, Wei‐Min Shen, Behnam Salemi, et al.. (2007). Modular Self-Reconfigurable Robot Systems. IEEE Robotics & Automation Magazine. 14(1). 43–52. 155 indexed citations
16.
Belta, Călin, Antonio Bicchi, Magnus Egerstedt, et al.. (2007). Symbolic planning and control of robot motion [Grand Challenges of Robotics]. IEEE Robotics & Automation Magazine. 14(1). 61–70. 256 indexed citations
17.
Klavins, Eric. (2006). Self-assembly from the point of view of its pieces. 16. 7 pp.–7 pp.. 10 indexed citations
18.
Bishop, Joshua D., Samuel A. Burden, Eric Klavins, et al.. (2005). Programmable parts: a demonstration of the grammatical approach to self-organization. 3684–3691. 57 indexed citations
19.
Klavins, Eric, Daniel E. Koditschek, & Robert Ghrist. (2000). Toward the Regulation and Composition of Cyclic Behaviors. ScholarlyCommons (University of Pennsylvania). 7 indexed citations
20.
Klavins, Eric, William C. Rounds, & Guo‐Qiang Zhang. (1998). Experimenting with power default reasoning. National Conference on Artificial Intelligence. 846–852. 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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