Jay Gowdy

19 papers receiving 394 citations

Peers

Jay Gowdy
Comparison fields: 5 of 62
  • Automotive Engineering 150
  • Computer Vision and Pattern Recognition 174
  • Industrial and Manufacturing Engineering 75
  • Instrumentation 18
  • Aerospace Engineering 108
Replace Nenad S. Jovicic with:
Nenad S. Jovicic Serbia
Jelena Kocić Serbia
Raquel Frizera Vassallo Brazil
Leopoldo Sánchez Spain
Linhai Xu China
Yeonsik Kang South Korea
Anna Petrovskaya United States
Sebastian Klemm Germany
Viktor Tihanyi Hungary
Pier Paolo Porta Italy
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Citations per year

Countries citing papers authored by Jay Gowdy

Since Specialization
Citations

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

Fields of papers citing papers by Jay Gowdy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jay Gowdy, 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 Jay Gowdy Line = papers co-authored together Jay Gowdy links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012105
2 200391
3 200250
4 199137
5 200136
6
Miniature Factories for Precision Assembly
199824
7 200519
8 200513
9 200212
10 200211
11 199711
12 19978
13
Design and Development of a Tabletop Precision Assembly System
20048
14 20037
15 20035
16 20004
17 19913
18 20182
19 19971
20 20180

About Jay Gowdy

Jay Gowdy is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering, Aerospace Engineering and Instrumentation, having authored 21 papers that have together received 447 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (9 papers), Flexible and Reconfigurable Manufacturing Systems (6 papers), Manufacturing Process and Optimization (6 papers), Robotic Path Planning Algorithms (5 papers), Robotics and Sensor-Based Localization (4 papers), Advanced Optical Sensing Technologies (3 papers), Modular Robots and Swarm Intelligence (3 papers) and Remote Sensing and LiDAR Applications (2 papers). The work is most often cited by research in Automotive Engineering (150 citations), Computer Vision and Pattern Recognition (174 citations), Industrial and Manufacturing Engineering (75 citations), Instrumentation (18 citations) and Aerospace Engineering (108 citations). Jay Gowdy has collaborated with scholars based in United States and France. Frequent co-authors include Ralph Hollis, Christoph Mertz, Chuck Thorpe, A.A. Rizzi, C. Thorpe, Chieh‐Chih Wang, Alfred A. Rizzi, Romuald Aufrère, Arne Suppé and Robert A. MacLachlan. Their work appears in journals such as Springer tracts in advanced robotics, The International Journal of Robotics Research, Engineering Applications of Artificial Intelligence, Journal of Field Robotics and Mechatronics.

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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