Kamil Saigol
- Computer Vision and Pattern Recognition top 10%
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Automotive Engineering top 10%
- Aerospace Engineering
- Co-authors
- Evangelos A. TheodorouYunpeng PanKeuntaek LeeChing-An ChengXinyan YanByron BootsGrady WilliamsJames M. Rehg
- Topics
- Reinforcement Learning in Robotics (5 papers)Advanced Control Systems Optimization (3 papers)Autonomous Vehicle Technology and Safety (3 papers)
- Cited by
- Automotive EngineeringComputer Vision and Pattern RecognitionControl and Systems Engineering
- Journals
- The International Journal of Robotics ResearchComputational IntelligencearXiv (Cornell University)
- Partner nations
- United StatesSwedenCanada
In The Last Decade
Kamil Saigol
8 papers receiving 281 citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 118
- Artificial Intelligence 115
- Control and Systems Engineering 109
- Automotive Engineering 105
- Aerospace Engineering 47
Countries citing papers authored by Kamil Saigol
This map shows the geographic impact of Kamil Saigol'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 Kamil Saigol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kamil Saigol more than expected).
Fields of papers citing papers by Kamil Saigol
This network shows the impact of papers produced by Kamil Saigol. 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 Kamil Saigol. The network helps show where Kamil Saigol may publish in the future.
Co-authorship network of co-authors of Kamil Saigol
This figure shows the co-authorship network connecting the top 25 collaborators of Kamil Saigol. A scholar is included among the top collaborators of Kamil Saigol 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 Kamil Saigol. Kamil Saigol is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 86 | |
| 3 | 45 | |
| 4 | 134 | |
| 5 | 3 | |
| 6 | Imitation Learning for Agile Autonomous Driving | 1 |
| 7 | 5 | |
| 8 | Agile Off-Road Autonomous Driving Using End-to-End Deep Imitation Learning. | 14 |
About Kamil Saigol
Kamil Saigol is a scholar working on Automotive Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 291 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Advanced Control Systems Optimization (3 papers) and Autonomous Vehicle Technology and Safety (3 papers). The work is most often cited by research in Automotive Engineering (105 citations), Computer Vision and Pattern Recognition (118 citations) and Control and Systems Engineering (109 citations). Kamil Saigol has collaborated with scholars based in United States, Sweden and Canada. Frequent co-authors include Evangelos A. Theodorou, Yunpeng Pan, Keuntaek Lee, Ching-An Cheng, Xinyan Yan, Byron Boots, Grady Williams, James M. Rehg, Brian Goldfain and Paul Drews. Their work appears in journals such as The International Journal of Robotics Research, Computational Intelligence and arXiv (Cornell University).
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.