Philip Long

636 citations
39 papers · 361 · h-index 10

Impact in

Papers in

Philip Long

33 papers receiving 347 citations

Peers

Philip Long
Comparison fields: 5 of 53
  • Control and Systems Engineering 261
  • Industrial and Manufacturing Engineering 49
  • Medical Laboratory Technology 6
  • Computer Vision and Pattern Recognition 85
  • Acoustics and Ultrasonics 3
Replace Ivan Lundberg with:
Ivan Lundberg Switzerland
Arne Wahrburg Germany
Marco Faroni Italy
Tianyu Ren China
Yunfei Dong China
Sabri Tosunoglu United States
Young-Loul Kim South Korea
E. Cheung United States
Alexander Alspach United States
Erik Kyrkjebø Norway
Philip Long relative to Ivan Lundberg Switzerland Ivan Lundberg's profile →
Citations per field
00.5×1.5×2.1×
Ivan Lundberg · 1×
Citations per year

Countries citing papers authored by Philip Long

Since Specialization
Citations

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

Fields of papers citing papers by Philip Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201755
2 201954
3 201936
4 201735
5 201423
6 201922
7 201316
8 201815
9 201912
10 202110
11 20198
12 20147
13 20216
14 20216
15 20216
16 20186
17 20235
18 20175
19 20125
20 20214

About Philip Long

Philip Long is a scholar working on Control and Systems Engineering, Biomedical Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 39 papers that have together received 361 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (19 papers), Robotic Mechanisms and Dynamics (17 papers), Robotic Locomotion and Control (11 papers), Robotic Path Planning Algorithms (8 papers), Modular Robots and Swarm Intelligence (7 papers), Soft Robotics and Applications (5 papers), Advanced Surface Polishing Techniques (3 papers) and Advanced Wireless Communication Techniques (3 papers). The work is most often cited by research in Control and Systems Engineering (261 citations), Industrial and Manufacturing Engineering (49 citations), Medical Laboratory Technology (6 citations), Computer Vision and Pattern Recognition (85 citations) and Acoustics and Ultrasonics (3 citations). Philip Long has collaborated with scholars based in United States, Ireland and France. Frequent co-authors include Stéphane Caro, Tahir Rasheed, Taşkın Padır, Wisama Khalil, Alexis Girin, Damien Chablat, Christine Chevallereau, Philippe Martinet, François Babin and David Ewen. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Robotics and Automation Letters, Robotica, IEEE Photonics Technology Letters and Journal of Mechanisms and Robotics.

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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