Zachary Kingston
- Computer Vision and Pattern Recognition top 2%
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Aerospace Engineering top 10%
- Mechanical Engineering
- Co-authors
- Lydia E. KavrakiMark MollNeil T. DantamSwarat ChaudhuriJames McLurkinGolnaz HabibiCarlos QuinteroMichael Gleicher
- Topics
- Robotic Path Planning Algorithms (21 papers)Robot Manipulation and Learning (12 papers)AI-based Problem Solving and Planning (10 papers)
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringArtificial Intelligence
- Journals
- The International Journal of Robotics ResearchIEEE Transactions on RoboticsIEEE Robotics and Automation Letters
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Zachary Kingston
23 papers receiving 550 citations
Peers
Comparison fields: 5 of 39
- Computer Vision and Pattern Recognition 411
- Control and Systems Engineering 343
- Artificial Intelligence 199
- Aerospace Engineering 93
- Mechanical Engineering 78
Countries citing papers authored by Zachary Kingston
This map shows the geographic impact of Zachary Kingston'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 Zachary Kingston with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zachary Kingston more than expected).
Fields of papers citing papers by Zachary Kingston
This network shows the impact of papers produced by Zachary Kingston. 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 Zachary Kingston. The network helps show where Zachary Kingston may publish in the future.
Co-authorship network of co-authors of Zachary Kingston
This figure shows the co-authorship network connecting the top 25 collaborators of Zachary Kingston. A scholar is included among the top collaborators of Zachary Kingston 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 Zachary Kingston. Zachary Kingston is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 3 | |
| 10 | 2 | |
| 11 | 9 | |
| 12 | 5 | |
| 13 | 37 | |
| 14 | 8 | |
| 15 | 16 | |
| 16 | 83 | |
| 17 | 118 | |
| 18 | 102 | |
| 19 | 9 | |
| 20 | 40 |
About Zachary Kingston
Zachary Kingston is a scholar working on Computer Vision and Pattern Recognition, Control and Systems Engineering and Software, having authored 26 papers that have together received 571 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (21 papers), Robot Manipulation and Learning (12 papers) and AI-based Problem Solving and Planning (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (411 citations), Control and Systems Engineering (343 citations) and Artificial Intelligence (199 citations). Zachary Kingston has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Lydia E. Kavraki, Mark Moll, Neil T. Dantam, Swarat Chaudhuri, James McLurkin, Golnaz Habibi, Carlos Quintero, Michael Gleicher, Daniel Rakita and Marc Toussaint. Their work appears in journals such as The International Journal of Robotics Research, IEEE Transactions on Robotics and IEEE Robotics and Automation Letters.
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.