Jeff Smith
Impact in
- Genetics top 10%
- Evolution and Genetic Dynamics
Papers in
-
- Evolutionary Game Theory and Cooperation 9
- Genetics 11
- Evolution and Genetic Dynamics 10
- Co-authors
- Edward P. Nikonowicz (3 shared papers)Joan E. Strassmann (4 shared papers)David C. Queller (4 shared papers)Adam Paszke (1 shared paper)Soumith Chintala (1 shared paper)J. David Van Dyken (2 shared papers)Rohan Varma (1 shared paper)Li Shen (1 shared paper)
- Journals
- Evolution (5 papers)Biochemistry (2 papers)Proceedings of the Royal Society B Biological Sciences (2 papers)The American Naturalist (1 paper)The Forum (1 paper)
- Partner nations
- United StatesSwitzerlandPoland
In The Last Decade
Jeff Smith
26 papers receiving 777 citations
Jeff Smith's Hit Papers
Peers
Comparison fields: 5 of 116
- Computational Mathematics 5
- Genetics 215
- Hardware and Architecture 47
- Endocrinology 32
- Computer Vision and Pattern Recognition 105
Countries citing papers authored by Jeff Smith
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
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-authors
The 25 scholars most cited alongside Jeff Smith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | PyTorch distributed Hit paper breakdown → | 2020 | 272 |
| 2 | 2001 | 110 | |
| 3 | 2000 | 62 | |
| 4 | 2010 | 61 | |
| 5 | 2014 | 54 | |
| 6 | 2011 | 31 | |
| 7 | 2010 | 30 | |
| 8 | 1998 | 29 | |
| 9 | 1984 | 26 | |
| 10 | 2011 | 24 | |
| 11 | 2016 | 19 | |
| 12 | 2014 | 15 | |
| 13 | 2007 | 13 | |
| 14 | 2013 | 13 | |
| 15 | 2011 | 12 | |
| 16 | 2020 | 8 | |
| 17 | 2013 | 5 | |
| 18 | 2015 | 3 | |
| 19 | 2004 | 2 | |
| 20 | 2021 | 2 |
About Jeff Smith
Jeff Smith is a scholar working on Sociology and Political Science, Genetics, Molecular Biology, Ecology, Evolution, Behavior and Systematics and Political Science and International Relations, having authored 26 papers that have together received 800 indexed citations. Recurring topics across this work include Evolution and Genetic Dynamics (10 papers), Evolutionary Game Theory and Cooperation (9 papers), Plant and animal studies (4 papers), RNA and protein synthesis mechanisms (3 papers), Bacteriophages and microbial interactions (3 papers), Electoral Systems and Political Participation (2 papers), Mathematical and Theoretical Epidemiology and Ecology Models (2 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Computational Mathematics (5 citations), Genetics (215 citations), Hardware and Architecture (47 citations), Endocrinology (32 citations) and Computer Vision and Pattern Recognition (105 citations). Jeff Smith has collaborated with scholars based in United States, Switzerland and Poland. Frequent co-authors include Edward P. Nikonowicz, Joan E. Strassmann, David C. Queller, Adam Paszke, Soumith Chintala, J. David Van Dyken, Rohan Varma, Li Shen, Teng Li and Peter C. Zee. Their work appears in journals such as Evolution, Biochemistry, Proceedings of the Royal Society B Biological Sciences, The American Naturalist and The Forum.
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.