Yevgen Chebotar
Impact in
-
- Robot Manipulation and Learning
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Reinforcement Learning in Robotics 5
-
- Robot Manipulation and Learning 5
- Advanced Control Systems Optimization 1
- Co-authors
- Stefan Schaal (5 shared papers)Sergey Levine (6 shared papers)Austin Waters (1 shared paper)Karol Hausman (7 shared papers)Gaurav S. Sukhatme (6 shared papers)Pierre Sermanet (2 shared papers)Corey Lynch (1 shared paper)Eric Jang (1 shared paper)
- Journals
- National Conference on Artificial Intelligence (1 paper)MPG.PuRe (Max Planck Society) (2 papers)arXiv (Cornell University) (2 papers)TUbilio (Technical University of Darmstadt) (2 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Yevgen Chebotar
15 papers receiving 912 citations
Yevgen Chebotar's Hit Papers
Peers
Comparison fields: 5 of 90
- Control and Systems Engineering 377
- Artificial Intelligence 459
- Computer Vision and Pattern Recognition 284
- Cognitive Neuroscience 190
- Human-Computer Interaction 34
Countries citing papers authored by Yevgen Chebotar
This map shows the geographic impact of Yevgen Chebotar'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 Yevgen Chebotar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yevgen Chebotar more than expected).
Fields of papers citing papers by Yevgen Chebotar
This network shows the impact of papers produced by Yevgen Chebotar. 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 Yevgen Chebotar. The network helps show where Yevgen Chebotar may publish in the future.
Co-authors
The 25 scholars most cited alongside Yevgen Chebotar, 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 | Time-Contrastive Networks: Self-Supervised Learning from Video Hit paper breakdown → | 2018 | 312 |
| 2 | 2015 | 142 | |
| 3 | 2016 | 104 | |
| 4 | 2017 | 80 | |
| 5 | 2017 | 60 | |
| 6 | 2017 | 59 | |
| 7 | 2016 | 59 | |
| 8 | 2014 | 44 | |
| 9 | Behind the Article: Recognizing Dialog Acts in Wikipedia Talk Pages | 2012 | 39 |
| 10 | 2024 | 27 | |
| 11 | BiGS: BioTac Grasp Stability Dataset | 2016 | 14 |
| 12 | Regrasping using Tactile Perception and Supervised Policy Learning | 2017 | 5 |
| 13 | Force Estimation and Slip Detection for Grip Control using a Biomimetic Tactile Sensor | 2015 | 5 |
| 14 | Scaling Up Multi-Task Robotic Reinforcement Learning | 2021 | 3 |
| 15 | 2024 | 2 | |
| 16 | 2023 | 0 |
About Yevgen Chebotar
Yevgen Chebotar is a scholar working on Artificial Intelligence, Control and Systems Engineering, Biomedical Engineering, Cognitive Neuroscience and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 955 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Robot Manipulation and Learning (5 papers), Muscle activation and electromyography studies (4 papers), Tactile and Sensory Interactions (3 papers), Advanced Sensor and Energy Harvesting Materials (3 papers), Advanced Control Systems Optimization (1 paper), Business Process Modeling and Analysis (1 paper) and Autonomous Vehicle Technology and Safety (1 paper). The work is most often cited by research in Control and Systems Engineering (377 citations), Artificial Intelligence (459 citations), Computer Vision and Pattern Recognition (284 citations), Cognitive Neuroscience (190 citations) and Human-Computer Interaction (34 citations). Yevgen Chebotar has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Stefan Schaal, Sergey Levine, Austin Waters, Karol Hausman, Gaurav S. Sukhatme, Pierre Sermanet, Corey Lynch, Eric Jang, Jasmine Hsu and Mrinal Kalakrishnan. Their work appears in journals such as National Conference on Artificial Intelligence, MPG.PuRe (Max Planck Society), arXiv (Cornell University) and TUbilio (Technical University of Darmstadt).
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.