Nate Koenig
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 10%
- Aerospace Engineering
- Artificial Intelligence
- Computer Graphics and Computer-Aided Design top 5%
- Co-authors
- Anthony FrancisKrista ReymannVincent VanhouckeSteven PetersJustin ManzoGill A. PrattIan ChenBrian Gerkey
- Topics
- Robotics and Automated Systems (3 papers)Speech and dialogue systems (2 papers)Modular Robots and Swarm Intelligence (1 paper)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- IEEE Transactions on Automation Science and Engineering2022 International Conference on Robotics and Automation (ICRA)
- Partner nations
- United States
In The Last Decade
Nate Koenig
6 papers receiving 264 citations
Hit Papers
Peers
Comparison fields: 5 of 45
- Computer Vision and Pattern Recognition 148
- Control and Systems Engineering 92
- Aerospace Engineering 57
- Artificial Intelligence 44
- Computer Graphics and Computer-Aided Design 38
Countries citing papers authored by Nate Koenig
This map shows the geographic impact of Nate Koenig'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 Nate Koenig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nate Koenig more than expected).
Fields of papers citing papers by Nate Koenig
This network shows the impact of papers produced by Nate Koenig. 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 Nate Koenig. The network helps show where Nate Koenig may publish in the future.
Co-authorship network of co-authors of Nate Koenig
This figure shows the co-authorship network connecting the top 25 collaborators of Nate Koenig. A scholar is included among the top collaborators of Nate Koenig 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 Nate Koenig. Nate Koenig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemsbreakdown → | 154 |
| 2 | 101 | |
| 3 | 1 | |
| 4 | 10 | |
| 5 | 2 | |
| 6 | 5 |
About Nate Koenig
Nate Koenig is a scholar working on Computer Graphics and Computer-Aided Design, Human-Computer Interaction and Control and Systems Engineering, having authored 6 papers that have together received 273 indexed citations. Recurring topics across this work include Robotics and Automated Systems (3 papers), Speech and dialogue systems (2 papers) and Modular Robots and Swarm Intelligence (1 paper). The work is most often cited by research in Computer Graphics and Computer-Aided Design (38 citations), Computer Vision and Pattern Recognition (148 citations) and Control and Systems Engineering (92 citations). Nate Koenig has collaborated with scholars based in United States. Frequent co-authors include Anthony Francis, Krista Reymann, Vincent Vanhoucke, Steven Peters, Justin Manzo, Gill A. Pratt, Ian Chen, Brian Gerkey, Carlos Agüero and Eric Krotkov. Their work appears in journals such as IEEE Transactions on Automation Science and Engineering and 2022 International Conference on Robotics and Automation (ICRA).
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.