Gregg Podnar

819 citations
28 papers · 583 · h-index 12

Impact in

Papers in

Gregg Podnar

25 papers receiving 546 citations

Peers

Gregg Podnar
Comparison fields: 5 of 78
  • Computer Vision and Pattern Recognition 136
  • Ophthalmology 59
  • Biomedical Engineering 276
  • Industrial and Manufacturing Engineering 48
  • Computer Graphics and Computer-Aided Design 16
Replace Gianmarc Coppola with:
Gianmarc Coppola Canada
Jianxun Zhang China
Siyu Guo China
Jacques Gangloff France
Weihang Zhang China
Alexandre Krupa France
Murat Tahtalı Australia
Manuel Ferreira Portugal
Gregg Podnar relative to Gianmarc Coppola Canada Gianmarc Coppola's profile →
Citations per field
00.5×1.5×2.0×
Gianmarc Coppola · 1×
Citations per year

Countries citing papers authored by Gregg Podnar

Since Specialization
Citations

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

Fields of papers citing papers by Gregg Podnar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gregg Podnar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gregg Podnar Line = papers co-authored together Gregg Podnar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011204
2 200663
3 200663
4 199446
5 199831
6 199726
7 200917
8 200614
9 200814
10 199813
11 200612
12 200612
13 200911
14 201011
15 201110
16 19969
17 20217
18 19954
19 20074
20 20074

About Gregg Podnar

Gregg Podnar is a scholar working on Mechanical Engineering, Ocean Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering and Artificial Intelligence, having authored 28 papers that have together received 583 indexed citations. Recurring topics across this work include Underwater Vehicles and Communication Systems (7 papers), Modular Robots and Swarm Intelligence (6 papers), Industrial Vision Systems and Defect Detection (4 papers), Maritime Navigation and Safety (4 papers), Image and Object Detection Techniques (3 papers), Space Exploration and Technology (2 papers), Water Quality Monitoring Technologies (2 papers) and Robotics and Sensor-Based Localization (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (136 citations), Ophthalmology (59 citations), Biomedical Engineering (276 citations), Industrial and Manufacturing Engineering (48 citations) and Computer Graphics and Computer-Aided Design (16 citations). Gregg Podnar has collaborated with scholars based in United States, Spain and Singapore. Frequent co-authors include Cameron N. Riviere, Mel Siegel, Louis A. Lobes, Brian C. Becker, Robert A. MacLachlan, Johnathan A. Engh, Alberto Elfes, John M. Dolan, Suiyang Khoo and Douglas Kondziolka. Their work appears in journals such as IEEE Transactions on Robotics, Industrial Robot the international journal of robotics research and application, Icarus, IEEE Instrumentation & Measurement Magazine and Research Showcase @ Carnegie Mellon University (Carnegie Mellon University).

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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