Paul Ruvolo
- Artificial Intelligence top 1%
- Computer Science Applications top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Management Science and Operations Research top 5%
- Cognitive Neuroscience top 10%
- Co-authors
- Javier R. MovellanJacob WhitehillTingfan WuEric EatonHaitham Bou AmmarMatthew E. TaylorMarian Stewart BartlettIan Fasel
- Topics
- Reinforcement Learning in Robotics (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)Speech and Audio Processing (4 papers)
- Cited by
- Computer Science ApplicationsArtificial IntelligenceComputer Vision and Pattern Recognition
- Partner nations
- United StatesItalyAustralia
In The Last Decade
Paul Ruvolo
33 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Artificial Intelligence 845
- Computer Science Applications 543
- Computer Vision and Pattern Recognition 301
- Management Science and Operations Research 176
- Cognitive Neuroscience 132
Countries citing papers authored by Paul Ruvolo
This map shows the geographic impact of Paul Ruvolo'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 Paul Ruvolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paul Ruvolo more than expected).
Fields of papers citing papers by Paul Ruvolo
This network shows the impact of papers produced by Paul Ruvolo. 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 Paul Ruvolo. The network helps show where Paul Ruvolo may publish in the future.
Co-authorship network of co-authors of Paul Ruvolo
This figure shows the co-authorship network connecting the top 25 collaborators of Paul Ruvolo. A scholar is included among the top collaborators of Paul Ruvolo 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 Paul Ruvolo. Paul Ruvolo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 51 | |
| 3 | 12 | |
| 4 | How do faculty partner while teaching interdisciplinary CS+X courses: models and experiences | 4 |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | Autonomous cross-domain knowledge transfer in lifelong policy gradient reinforcement learning | 30 |
| 9 | 23 | |
| 10 | 37 | |
| 11 | Online Multi-Task Learning for Policy Gradient Methods | 74 |
| 12 | ELLA: An Efficient Lifelong Learning Algorithm | 144 |
| 13 | Scalable Lifelong Learning with Active Task Selection | 7 |
| 14 | 39 | |
| 15 | 38 | |
| 16 | 18 | |
| 17 | 29 | |
| 18 | Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertisebreakdown → | 662 |
| 19 | 18 | |
| 20 | Optimization on a Budget: A Reinforcement Learning Approach | 7 |
About Paul Ruvolo
Paul Ruvolo is a scholar working on Pharmacy, Computer Science Applications and Architecture, having authored 34 papers that have together received 1.4k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (6 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Speech and Audio Processing (4 papers). The work is most often cited by research in Computer Science Applications (543 citations), Artificial Intelligence (845 citations) and Computer Vision and Pattern Recognition (301 citations). Paul Ruvolo has collaborated with scholars based in United States, Italy and Australia. Frequent co-authors include Javier R. Movellan, Jacob Whitehill, Tingfan Wu, Eric Eaton, Haitham Bou Ammar, Matthew E. Taylor, Marian Stewart Bartlett, Ian Fasel, Daniel S. Messinger and Naomi V. Ekas. Their work appears in journals such as PLoS ONE, Neural Networks and Pattern Recognition 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.