Shane Griffith
Impact in
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Explainable Artificial Intelligence (XAI)
- Control and Systems Engineering top 10%
- Robot Manipulation and Learning
Papers in
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- Robot Manipulation and Learning 5
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- Reinforcement Learning in Robotics 2
- Domain Adaptation and Few-Shot Learning 2
- Co-authors
- K.A. Subramanian (1 shared paper)Charles L. Isbell (1 shared paper)Andrea L. Thomaz (1 shared paper)Jonathan Scholz (1 shared paper)Alexander Stoytchev (6 shared papers)Jivko Sinapov (4 shared papers)Cédric Pradalier (4 shared papers)Georges Chahine (1 shared paper)
- Journals
- The International Journal of Robotics Research (3 papers)Journal of Field Robotics (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)SMARTech Repository (Georgia Institute of Technology) (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Shane Griffith
11 papers receiving 294 citations
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 192
- Control and Systems Engineering 131
- Computer Vision and Pattern Recognition 68
- Health Informatics 4
- Computer Science Applications 14
Countries citing papers authored by Shane Griffith
This map shows the geographic impact of Shane Griffith'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 Shane Griffith with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane Griffith more than expected).
Fields of papers citing papers by Shane Griffith
This network shows the impact of papers produced by Shane Griffith. 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 Shane Griffith. The network helps show where Shane Griffith may publish in the future.
Co-authors
The 9 scholars most cited alongside Shane Griffith, 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 | Policy Shaping: Integrating Human Feedback with Reinforcement Learning | 2013 | 166 |
| 2 | 2011 | 46 | |
| 3 | 2011 | 32 | |
| 4 | 2009 | 28 | |
| 5 | 2017 | 15 | |
| 6 | 2016 | 8 | |
| 7 | 2010 | 7 | |
| 8 | 2011 | 6 | |
| 9 | 2016 | 4 | |
| 10 | 2019 | 2 | |
| 11 | 2010 | 2 |
About Shane Griffith
Shane Griffith is a scholar working on Control and Systems Engineering, Artificial Intelligence, Computer Vision and Pattern Recognition, Ocean Engineering and Cognitive Neuroscience, having authored 11 papers that have together received 316 indexed citations. Recurring topics across this work include Robot Manipulation and Learning (5 papers), Robotics and Sensor-Based Localization (2 papers), Remote Sensing and LiDAR Applications (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), Reinforcement Learning in Robotics (2 papers), Language and cultural evolution (2 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Gaze Tracking and Assistive Technology (1 paper). The work is most often cited by research in Artificial Intelligence (192 citations), Control and Systems Engineering (131 citations), Computer Vision and Pattern Recognition (68 citations), Health Informatics (4 citations) and Computer Science Applications (14 citations). Shane Griffith has collaborated with scholars based in United States and France. Frequent co-authors include K.A. Subramanian, Charles L. Isbell, Andrea L. Thomaz, Jonathan Scholz, Alexander Stoytchev, Jivko Sinapov, Cédric Pradalier, Georges Chahine and Frank Dellaert. Their work appears in journals such as The International Journal of Robotics Research, Journal of Field Robotics, Proceedings of the AAAI Conference on Artificial Intelligence and SMARTech Repository (Georgia Institute of Technology).
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.