Brent Yi
Impact in
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- Robotic Path Planning Algorithms
- Human Pose and Action Recognition
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- Robot Manipulation and Learning
Papers in
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- Robot Manipulation and Learning 2
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- Multimodal Machine Learning Applications 1
- Human Pose and Action Recognition 1
- Co-authors
- Jeannette Bohg (2 shared papers)Michelle A. Lee (1 shared paper)Pieter Abbeel (1 shared paper)Stephen McKinley (1 shared paper)David V. Gealy (1 shared paper)Toki Migimatsu (1 shared paper)Jitendra Malik (3 shared papers)Weijia Zeng (1 shared paper)
- Journals
- 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)
- Partner nations
- United StatesGermanyChina
In The Last Decade
Brent Yi
5 papers receiving 47 citations
Peers
Comparison fields: 5 of 21
- Computer Vision and Pattern Recognition 23
- Control and Systems Engineering 20
- Human-Computer Interaction 4
- Computer Graphics and Computer-Aided Design 2
- Geology 3
Countries citing papers authored by Brent Yi
This map shows the geographic impact of Brent Yi'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 Brent Yi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brent Yi more than expected).
Fields of papers citing papers by Brent Yi
This network shows the impact of papers produced by Brent Yi. 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 Brent Yi. The network helps show where Brent Yi may publish in the future.
Co-authors
The 17 scholars most cited alongside Brent Yi, 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 | 2021 | 16 | |
| 2 | 2022 | 11 | |
| 3 | 2019 | 10 | |
| 4 | 2025 | 6 | |
| 5 | 2023 | 4 | |
| 6 | 2025 | 0 | |
| 7 | 2025 | 0 |
About Brent Yi
Brent Yi is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Aerospace Engineering, Human-Computer Interaction and Automotive Engineering, having authored 7 papers that have together received 47 indexed citations. Recurring topics across this work include Virtual Reality Applications and Impacts (2 papers), Robotics and Sensor-Based Localization (2 papers), Robot Manipulation and Learning (2 papers), 3D Shape Modeling and Analysis (1 paper), Multimodal Machine Learning Applications (1 paper), Human Pose and Action Recognition (1 paper), Visual and Cognitive Learning Processes (1 paper) and Ergonomics and Musculoskeletal Disorders (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (23 citations), Control and Systems Engineering (20 citations), Human-Computer Interaction (4 citations), Computer Graphics and Computer-Aided Design (2 citations) and Geology (3 citations). Brent Yi has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Jeannette Bohg, Michelle A. Lee, Pieter Abbeel, Stephen McKinley, David V. Gealy, Toki Migimatsu, Jitendra Malik, Weijia Zeng, Qiyang Li and Haozhi Qi. Their work appears in journals such as 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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.