Deirdre Quillen
- Artificial Intelligence top 10%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Management Science and Operations Research
- Co-authors
- Sergey LevineChelsea FinnKate RakellyAurick ZhouAlex IrpanEric JangAlexander HerzogDmitry Kalashnikov
- Topics
- Reinforcement Learning in Robotics (3 papers)Robot Manipulation and Learning (1 paper)Muscle activation and electromyography studies (1 paper)
- Cited by
- Artificial IntelligenceControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- arXiv (Cornell University)
- Partner nations
- United States
In The Last Decade
Deirdre Quillen
3 papers receiving 160 citations
Peers
Comparison fields: 5 of 41
- Artificial Intelligence 118
- Control and Systems Engineering 72
- Computer Vision and Pattern Recognition 46
- Biomedical Engineering 35
- Management Science and Operations Research 11
Countries citing papers authored by Deirdre Quillen
This map shows the geographic impact of Deirdre Quillen'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 Deirdre Quillen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Deirdre Quillen more than expected).
Fields of papers citing papers by Deirdre Quillen
This network shows the impact of papers produced by Deirdre Quillen. 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 Deirdre Quillen. The network helps show where Deirdre Quillen may publish in the future.
Co-authorship network of co-authors of Deirdre Quillen
This figure shows the co-authorship network connecting the top 25 collaborators of Deirdre Quillen. A scholar is included among the top collaborators of Deirdre Quillen 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 Deirdre Quillen. Deirdre Quillen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning | 27 |
| 2 | 75 | |
| 3 | QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation | 71 |
About Deirdre Quillen
Deirdre Quillen is a scholar working on Artificial Intelligence, Control and Systems Engineering and Biomedical Engineering, having authored 3 papers that have together received 173 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Robot Manipulation and Learning (1 paper) and Muscle activation and electromyography studies (1 paper). The work is most often cited by research in Artificial Intelligence (118 citations), Control and Systems Engineering (72 citations) and Computer Vision and Pattern Recognition (46 citations). Deirdre Quillen has collaborated with scholars based in United States. Frequent co-authors include Sergey Levine, Chelsea Finn, Kate Rakelly, Aurick Zhou, Alex Irpan, Eric Jang, Alexander Herzog, Dmitry Kalashnikov, Vincent Vanhoucke and Peter Pástor. Their work appears in journals such as 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.