Zachary Kingston
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- Robotic Path Planning Algorithms 21
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- Robot Manipulation and Learning 12
- Robotic Mechanisms and Dynamics 3
- Artificial Intelligence top 10%
- AI-based Problem Solving and Planning 10
- Machine Learning and Algorithms 2
- Aerospace Engineering top 10%
- Robotics and Sensor-Based Localization 5
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- Modular Robots and Swarm Intelligence 2
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- Model-Driven Software Engineering Techniques 2
- Co-authors
- Lydia E. KavrakiMark MollNeil T. DantamSwarat ChaudhuriJames McLurkinGolnaz HabibiCarlos QuinteroMichael Gleicher
- Cited by
- Computer Vision and Pattern RecognitionControl and Systems EngineeringArtificial Intelligence
- Journals
- The International Journal of Robotics Research (2 papers)IEEE Transactions on Robotics (1 paper)IEEE Robotics and Automation Letters (2 papers)
- 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
- Industrial and Manufacturing Engineering 42
- Aerospace Engineering 93
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
The 25 scholars most cited alongside Zachary Kingston, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 8 | |
| 6 | 2024 | 4 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2023 | 3 | |
| 10 | 2023 | 2 | |
| 11 | 2022 | 9 | |
| 12 | 2021 | 5 | |
| 13 | 2021 | 37 | |
| 14 | 2021 | 8 | |
| 15 | 2020 | 16 | |
| 16 | 2018 | 83 | |
| 17 | 2018 | 118 | |
| 18 | 2016 | 102 | |
| 19 | 2015 | 9 | |
| 20 | 2015 | 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), AI-based Problem Solving and Planning (10 papers), Robotics and Sensor-Based Localization (5 papers), Robotic Mechanisms and Dynamics (3 papers), Modular Robots and Swarm Intelligence (2 papers), Model-Driven Software Engineering Techniques (2 papers) and Machine Learning and Algorithms (2 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.