James Uplinger

18 total papers · 702 total citations
4 papers, 574 citations indexed

About

James Uplinger is a scholar working on Biomedical Engineering, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, James Uplinger has authored 4 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Biomedical Engineering, 2 papers in Computational Mechanics and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in James Uplinger's work include Nanopore and Nanochannel Transport Studies (3 papers), Ion-surface interactions and analysis (2 papers) and Video Surveillance and Tracking Methods (1 paper). James Uplinger is often cited by papers focused on Nanopore and Nanochannel Transport Studies (3 papers), Ion-surface interactions and analysis (2 papers) and Video Surveillance and Tracking Methods (1 paper). James Uplinger collaborates with scholars based in United States. James Uplinger's co-authors include Daniel Fologea, Jiali Li, Brian Thomas, David S. McNabb, Eric Brandin, Daniel Branton, Ryan Rollings, Heesung Kwon, James Dean Brown and Priya Narayanan and has published in prestigious journals such as Nano Letters, IEEE Transactions on Image Processing and Electrophoresis.

In The Last Decade

James Uplinger

4 papers receiving 555 citations

Hit Papers

Slowing DNA Translocation... 2005 2026 2012 2019 2005 100 200 300 400

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
James Uplinger 553 207 156 144 111 4 574
Brian Thomas 474 0.9× 186 0.9× 135 0.9× 121 0.8× 92 0.8× 10 502
Rolf Timp 487 0.9× 184 0.9× 100 0.6× 99 0.7× 68 0.6× 6 546
L. Sexton 577 1.0× 210 1.0× 116 0.7× 136 0.9× 91 0.8× 8 617
Santoshi Nandivada 504 0.9× 121 0.6× 153 1.0× 169 1.2× 63 0.6× 6 529
Olivia M. Eggenberger 628 1.1× 161 0.8× 186 1.2× 222 1.5× 83 0.7× 9 678
David J. Niedzwiecki 533 1.0× 183 0.9× 145 0.9× 159 1.1× 58 0.5× 15 583
Kaimeng Zhou 552 1.0× 212 1.0× 67 0.4× 61 0.4× 89 0.8× 7 600
Pradeep Waduge 397 0.7× 146 0.7× 117 0.8× 112 0.8× 42 0.4× 9 535
Kumar Sarthak 437 0.8× 86 0.4× 107 0.7× 270 1.9× 42 0.4× 7 553
B. Schiedt 596 1.1× 376 1.8× 94 0.6× 59 0.4× 84 0.8× 12 693

Countries citing papers authored by James Uplinger

Since Specialization
Citations

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

Fields of papers citing papers by James Uplinger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of James Uplinger

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

All Works

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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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