Shane Barratt
Impact in
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- Autonomous Vehicle Technology and Safety
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- Air Traffic Management and Optimization
- Aerospace and Aviation Technology
Papers in
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- Robot Manipulation and Learning 1
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- Face and Expression Recognition 2
- Co-authors
- Stephen Boyd (7 shared papers)Mykel J. Kochenderfer (1 shared paper)Brandon Amos (1 shared paper)Akshay Agrawal (2 shared papers)Steven Diamond (1 shared paper)J. Zico Kolter (1 shared paper)Alex X. Lee (1 shared paper)Pieter Abbeel (1 shared paper)
- Journals
- Optimization and Engineering (2 papers)Journal of Machine Learning Research (1 paper)IEEE Transactions on Intelligent Transportation Systems (1 paper)Journal of Global Optimization (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Shane Barratt
7 papers receiving 145 citations
Peers
Comparison fields: 5 of 48
- Automotive Engineering 32
- Aerospace Engineering 65
- Safety, Risk, Reliability and Quality 20
- Computational Mathematics 1
- Artificial Intelligence 54
Countries citing papers authored by Shane Barratt
This map shows the geographic impact of Shane Barratt'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 Barratt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shane Barratt more than expected).
Fields of papers citing papers by Shane Barratt
This network shows the impact of papers produced by Shane Barratt. 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 Barratt. The network helps show where Shane Barratt may publish in the future.
Co-authors
The 9 scholars most cited alongside Shane Barratt, 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 | 2018 | 69 | |
| 2 | 2019 | 32 | |
| 3 | 2019 | 30 | |
| 4 | 2015 | 9 | |
| 5 | A Distributed Method for Fitting Laplacian Regularized Stratified Models | 2021 | 4 |
| 6 | 2022 | 3 | |
| 7 | 2022 | 3 | |
| 8 | 2023 | 0 |
About Shane Barratt
Shane Barratt is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Aerospace Engineering and Statistics and Probability, having authored 8 papers that have together received 150 indexed citations. Recurring topics across this work include Face and Expression Recognition (2 papers), Statistical Methods and Inference (2 papers), Remote-Sensing Image Classification (1 paper), Capital Investment and Risk Analysis (1 paper), Robotics and Sensor-Based Localization (1 paper), Robot Manipulation and Learning (1 paper), Advanced Statistical Methods and Models (1 paper) and Aerospace and Aviation Technology (1 paper). The work is most often cited by research in Automotive Engineering (32 citations), Aerospace Engineering (65 citations), Safety, Risk, Reliability and Quality (20 citations), Computational Mathematics (1 citation) and Artificial Intelligence (54 citations). Shane Barratt has collaborated with scholars based in United States and Israel. Frequent co-authors include Stephen Boyd, Mykel J. Kochenderfer, Brandon Amos, Akshay Agrawal, Steven Diamond, J. Zico Kolter, Alex X. Lee, Pieter Abbeel and Walaa M. Moursi. Their work appears in journals such as Optimization and Engineering, Journal of Machine Learning Research, IEEE Transactions on Intelligent Transportation Systems, Journal of Global Optimization and 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.