Andrea Bajcsy
- Control and Systems Engineering top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Social Psychology
- Cognitive Neuroscience
- Co-authors
- Anca D. DraganDylan P. LoseyMarcia K. O’MalleyClaire J. TomlinDavid Fridovich-KeilJaime F. FisacSteven WangSylvia Herbert
- Topics
- Reinforcement Learning in Robotics (7 papers)Robot Manipulation and Learning (5 papers)Human-Automation Interaction and Safety (3 papers)
- Journals
- The International Journal of Robotics ResearchInternational Journal of Human-Computer StudiesIEEE Robotics and Automation Letters
- Partner nations
- United StatesNetherlands
In The Last Decade
Andrea Bajcsy
18 papers receiving 290 citations
Peers
Comparison fields: 5 of 60
- Control and Systems Engineering 122
- Artificial Intelligence 115
- Computer Vision and Pattern Recognition 60
- Social Psychology 52
- Cognitive Neuroscience 51
Countries citing papers authored by Andrea Bajcsy
This map shows the geographic impact of Andrea Bajcsy'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 Andrea Bajcsy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrea Bajcsy more than expected).
Fields of papers citing papers by Andrea Bajcsy
This network shows the impact of papers produced by Andrea Bajcsy. 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 Andrea Bajcsy. The network helps show where Andrea Bajcsy may publish in the future.
Co-authorship network of co-authors of Andrea Bajcsy
This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Bajcsy. A scholar is included among the top collaborators of Andrea Bajcsy 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 Andrea Bajcsy. Andrea Bajcsy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 10 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 8 | |
| 10 | 27 | |
| 11 | 1 | |
| 12 | 17 | |
| 13 | 79 | |
| 14 | 41 | |
| 15 | 1 | |
| 16 | Learning Robot Objectives from Physical Human Interaction | 38 |
| 17 | 36 | |
| 18 | 21 | |
| 19 | 2 |
About Andrea Bajcsy
Andrea Bajcsy is a scholar working on Human Factors and Ergonomics, Human-Computer Interaction and Social Psychology, having authored 19 papers that have together received 298 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Robot Manipulation and Learning (5 papers) and Human-Automation Interaction and Safety (3 papers). The work is most often cited by research in Human-Computer Interaction (38 citations), Control and Systems Engineering (122 citations) and Automotive Engineering (47 citations). Andrea Bajcsy has collaborated with scholars based in United States and Netherlands. Frequent co-authors include Anca D. Dragan, Dylan P. Losey, Marcia K. O’Malley, Claire J. Tomlin, David Fridovich-Keil, Jaime F. Fisac, Steven Wang, Sylvia Herbert, Ran Tian and Masayoshi Tomizuka. Their work appears in journals such as The International Journal of Robotics Research, International Journal of Human-Computer Studies 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.