Brian Hou
Impact in
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- Robot Manipulation and Learning
- Robotics and Automated Systems
- Computer Science Applications top 10%
- Teaching and Learning Programming
- Online Learning and Analytics
Papers in
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- Robotic Path Planning Algorithms 6
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- Teaching and Learning Programming 3
- Online Learning and Analytics 1
- Co-authors
- Jeffrey Mahler (2 shared papers)Ken Y. Goldberg (2 shared papers)Florian T. Pokorny (2 shared papers)Melrose Roderick (1 shared paper)Torsten Kröger (1 shared paper)James Kuffner (1 shared paper)Kai Kohlhoff (1 shared paper)Michael Laskey (1 shared paper)
- Journals
- Proceedings - IEEE International Conference on Robotics and Automation/Proceedings (5 papers)2022 IEEE 18th International Conference on Automation Science and Engineering (CASE) (1 paper)ACM Conference on Learning @ Scale (L@S) (2 papers)IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2 papers)Proceedings of the International Conference on Automated Planning and Scheduling (1 paper)
- Partner nations
- United States
In The Last Decade
Brian Hou
12 papers receiving 347 citations
Brian Hou's Hit Papers
Peers
Comparison fields: 5 of 25
- Control and Systems Engineering 261
- Computer Science Applications 29
- Computer Vision and Pattern Recognition 47
- Artificial Intelligence 33
- Information Systems 10
Countries citing papers authored by Brian Hou
This map shows the geographic impact of Brian Hou'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 Brian Hou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Brian Hou more than expected).
Fields of papers citing papers by Brian Hou
This network shows the impact of papers produced by Brian Hou. 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 Brian Hou. The network helps show where Brian Hou may publish in the future.
Co-authors
The 20 scholars most cited alongside Brian Hou, 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 | Dex-Net 1.0: A cloud-based network of 3D objects for robust grasp planning using a Multi-Armed Bandit model with correlated rewards Hit paper breakdown → | 2016 | 270 |
| 2 | 2015 | 14 | |
| 3 | 2016 | 14 | |
| 4 | 2023 | 12 | |
| 5 | 2016 | 11 | |
| 6 | 2020 | 9 | |
| 7 | 2017 | 7 | |
| 8 | 2022 | 5 | |
| 9 | 2016 | 4 | |
| 10 | 2021 | 2 | |
| 11 | 2022 | 2 | |
| 12 | 2024 | 2 |
About Brian Hou
Brian Hou is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications, Control and Systems Engineering, Information Systems and Artificial Intelligence, having authored 12 papers that have together received 352 indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (6 papers), Teaching and Learning Programming (3 papers), Robot Manipulation and Learning (2 papers), Educational Technology and Assessment (1 paper), Reinforcement Learning in Robotics (1 paper) and Online Learning and Analytics (1 paper). The work is most often cited by research in Control and Systems Engineering (261 citations), Computer Science Applications (29 citations), Computer Vision and Pattern Recognition (47 citations), Artificial Intelligence (33 citations) and Information Systems (10 citations). Brian Hou has collaborated with scholars based in United States. Frequent co-authors include Jeffrey Mahler, Ken Y. Goldberg, Florian T. Pokorny, Melrose Roderick, Torsten Kröger, James Kuffner, Kai Kohlhoff, Michael Laskey, Mathieu Aubry and Siddhartha S Srinivasa. Their work appears in journals such as Proceedings - IEEE International Conference on Robotics and Automation/Proceedings, 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), ACM Conference on Learning @ Scale (L@S), IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and Proceedings of the International Conference on Automated Planning and Scheduling.
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.