James G. Stevens

858 total citations
14 papers, 680 citations indexed

About

James G. Stevens is a scholar working on Biomedical Engineering, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, James G. Stevens has authored 14 papers receiving a total of 680 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Biomedical Engineering, 3 papers in Artificial Intelligence and 3 papers in Mechanical Engineering. Recurrent topics in James G. Stevens's work include Neural Networks and Applications (3 papers), Catalysis for Biomass Conversion (3 papers) and Phase Equilibria and Thermodynamics (3 papers). James G. Stevens is often cited by papers focused on Neural Networks and Applications (3 papers), Catalysis for Biomass Conversion (3 papers) and Phase Equilibria and Thermodynamics (3 papers). James G. Stevens collaborates with scholars based in United Kingdom, United States and Spain. James G. Stevens's co-authors include Peter Lewis, Richard A. Bourne, Martyn Poliakoff, M. V. Twigg, Jie Ke, Paul D. Beer, Andrew Docker, J.A.R. Renuncio, María José Tenorio and Albertina Cabañas and has published in prestigious journals such as Angewandte Chemie International Edition, Journal of the American Statistical Association and Chemical Communications.

In The Last Decade

James G. Stevens

14 papers receiving 648 citations

Peers

James G. Stevens
Comparison fields: 5 of 91
  • Biomedical Engineering 345
  • Mechanical Engineering 161
  • Materials Chemistry 120
  • Catalysis 110
  • Organic Chemistry 103
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Citations per field, relative to James G. Stevens
James G. Stevens · 1×
Citations per year, relative to James G. Stevens
James G. Stevens · 1×

Countries citing papers authored by James G. Stevens

Since Specialization
Citations

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

Fields of papers citing papers by James G. Stevens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James G. Stevens. 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 James G. Stevens. The network helps show where James G. Stevens may publish in the future.

Co-authorship network of co-authors of James G. Stevens

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

All Works

14 of 14 papers shown
# Work Indexed citations
1 26
2 8
3 3
4 35
5 21
6 130
7 36
8 37
9 2
10 158
11 8
12 165
13 44
14
An Investigation of Multivariate Adaptive Regression Splines for Modeling and Analysis of Univariate and Semi-Multivariate Time Series Systems
7

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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