Jeff Smith

1.7k total citations · 1 hit paper
26 papers, 754 citations indexed

About

Jeff Smith is a scholar working on Sociology and Political Science, Genetics and Molecular Biology. According to data from OpenAlex, Jeff Smith has authored 26 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Sociology and Political Science, 11 papers in Genetics and 6 papers in Molecular Biology. Recurrent topics in Jeff Smith's work include Evolution and Genetic Dynamics (10 papers), Evolutionary Game Theory and Cooperation (9 papers) and Plant and animal studies (4 papers). Jeff Smith is often cited by papers focused on Evolution and Genetic Dynamics (10 papers), Evolutionary Game Theory and Cooperation (9 papers) and Plant and animal studies (4 papers). Jeff Smith collaborates with scholars based in United States, United Kingdom and Switzerland. Jeff Smith's co-authors include Edward P. Nikonowicz, Joan E. Strassmann, David C. Queller, J. David Van Dyken, Teng Li, Li Shen, Adam Paszke, Rohan Varma, Soumith Chintala and Peter C. Zee and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and Biochemistry.

In The Last Decade

Jeff Smith

26 papers receiving 737 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

PyTorch distributed

2020 248 citations Li Shen, Rohan Varma et al. Proceedings of the VLDB Endowment profile →

Peers

Jeff Smith

MB

GENET

SPS

AI

CVPR

David B. Knoester United States

Erik Rauch United States

Thomas Anantharaman United States

James R. Giles United States

Arend Hintze United States

Mark Howison United States

Steven Myers United States

Thomas E. Gorochowski United Kingdom

Merav Parter Israel

Andrew Butterfield Ireland

David B. Knoester United States

Jeff Smith

174 ×0.7

MB

225 ×1.0

GENET

137 ×0.8

SPS

184 ×1.4

AI

14 ×0.1

CVPR

Citations per year, relative to Jeff Smith Jeff Smith (= 1×) peers David B. Knoester

Countries citing papers authored by Jeff Smith

Since Specialization

Citations

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

Fields of papers citing papers by Jeff Smith

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jeff Smith

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Smith, Jeff & R. Fredrik Inglis. (2021). Evaluating kin and group selection as tools for quantitative analysis of microbial data. Proceedings of the Royal Society B Biological Sciences. 288(1951). 20201657–20201657. 2 indexed citations

2.

Smith, Jeff, et al.. (2020). Northern Populism: Causes and Consequences of the New Ordered Outlook. The School of Public Policy Publications. 13. 7 indexed citations

3.

Smith, Jeff, et al.. (2020). Northern Populism: Causes and Consequences of the New Ordered Outlook. SHILAP Revista de lepidopterología. 1 indexed citations

4.

Shen, Li, Rohan Varma, Teng Li, et al.. (2020). PyTorch distributed. Proceedings of the VLDB Endowment. 13(12). 3005–3018. 248 indexed citations breakdown →

5.

Smith, Jeff. (2018). From the “Ayotte Evasion” to Rejecting Trump: Senator Kelly Ayotte’s Post-Crisis Discourse of Renewal. Communication Quarterly. 66(2). 117–137. 1 indexed citations

6.

Smith, Jeff, Joan E. Strassmann, & David C. Queller. (2016). Fine-scale spatial ecology drives kin selection relatedness among cooperating amoebae. Evolution. 70(4). 848–859. 17 indexed citations

7.

DiSalvo, Susanne, Debra A. Brock, Jeff Smith, David C. Queller, & Joan E. Strassmann. (2014). In the social amoeba Dictyostelium discoideum, density, not farming status, determines predatory success on unpalatable Escherichia coli. BMC Microbiology. 14(1). 328–328. 14 indexed citations

8.

Smith, Jeff, David C. Queller, & Joan E. Strassmann. (2014). Fruiting bodies of the social amoeba Dictyostelium discoideum increase spore transport by Drosophila. BMC Evolutionary Biology. 14(1). 105–105. 51 indexed citations

9.

Smith, Jeff & David C. Kimball. (2013). Barking Louder: Interest Groups in the 2012 Election. The Forum. 10(4). 80–90. 2 indexed citations

10.

Smith, Jeff, et al.. (2013). Measuring Cheating, Fitness, and Segregation in Dictyostelium discoideum. Methods in molecular biology. 983. 231–248. 5 indexed citations

11.

Smith, Jeff, J. David Van Dyken, & Gregory J. Velicer. (2013). NONADAPTIVE PROCESSES CAN CREATE THE APPEARANCE OF FACULTATIVE CHEATING IN MICROBES. Evolution. 68(3). 816–826. 13 indexed citations

12.

Sydserff, S G, Min Ding, David C. Perry, et al.. (2011). Ultra-low exposure to alpha-7 nicotinic acetylcholine receptor partial agonists elicits an improvement in cognition that corresponds with an increase in alpha-7 receptor expression in rodents: implications for low dose clinical efficacy. Neuroscience. 186. 76–87. 29 indexed citations

13.

Smith, Jeff. (2011). TRAGEDY OF THE COMMONS AMONG ANTIBIOTIC RESISTANCE PLASMIDS. Evolution. 66(4). 1269–1274. 12 indexed citations

14.

Maier, Donna L., Min Ding, Emily B. Einstein, et al.. (2011). Pre-clinical validation of a novel alpha-7 nicotinic receptor radiotracer, [3H]AZ11637326: Target localization, biodistribution and ligand occupancy in the rat brain. Neuropharmacology. 61(1-2). 161–171. 20 indexed citations

15.

Smith, Jeff. (2011). DISTINGUISHING CAUSES OF VIRULENCE EVOLUTION: REPLY TO ALIZON AND MICHALAKIS. Evolution. 65(12). 3639–3641. 2 indexed citations

16.

Smith, Jeff, J. David Van Dyken, & Peter C. Zee. (2010). A Generalization of Hamilton’s Rule for the Evolution of Microbial Cooperation. Science. 328(5986). 1700–1703. 58 indexed citations

17.

Smith, Jeff. (2010). SUPERINFECTION DRIVES VIRULENCE EVOLUTION IN EXPERIMENTAL POPULATIONS OF BACTERIA AND PLASMIDS. Evolution. 65(3). 831–841. 30 indexed citations

18.

Smith, Jeff. (2007). A Gene’s‐Eye View of Symbiont Transmission. The American Naturalist. 170(4). 542–550. 13 indexed citations

19.

Smith, Jeff, et al.. (2004). Perspectives on designing design managers. Design Management Review. 15(2). 74–79. 2 indexed citations

20.

Smith, Jeff. (2001). The social evolution of bacterial pathogenesis. Proceedings of the Royal Society B Biological Sciences. 268(1462). 61–69. 106 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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