Justin Fu
Impact in
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- Autonomous Vehicle Technology and Safety
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Topic Modeling
- Speech and dialogue systems
Papers in
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- Reinforcement Learning in Robotics 7
- Adversarial Robustness in Machine Learning 3
- Speech and dialogue systems 2
- AI in Service Interactions 2
- Topic Modeling 2
- Data Stream Mining Techniques 1
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- Autonomous Vehicle Technology and Safety 3
- Co-authors
- Sergey Levine (10 shared papers)George Tucker (3 shared papers)Aviral Kumar (3 shared papers)Dragomir Anguelov (3 shared papers)Shimon Whiteson (2 shared papers)Yiren Lu (2 shared papers)Sherry X. Yang (2 shared papers)Siddharth Verma (1 shared paper)
- Journals
- Journal of Artificial Intelligence Research (1 paper)Thin Solid Films (1 paper)arXiv (Cornell University) (7 papers)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Justin Fu
13 papers receiving 139 citations
Peers
Comparison fields: 5 of 36
- Automotive Engineering 36
- Artificial Intelligence 96
- Computer Vision and Pattern Recognition 33
- Control and Systems Engineering 35
- Management Science and Operations Research 13
Countries citing papers authored by Justin Fu
This map shows the geographic impact of Justin Fu'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 Justin Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Justin Fu more than expected).
Fields of papers citing papers by Justin Fu
This network shows the impact of papers produced by Justin Fu. 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 Justin Fu. The network helps show where Justin Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Justin Fu, 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 | Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction | 2019 | 30 |
| 2 | 2022 | 29 | |
| 3 | 2023 | 25 | |
| 4 | 2017 | 24 | |
| 5 | 2022 | 12 | |
| 6 | 2021 | 7 | |
| 7 | Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition | 2018 | 4 |
| 8 | 2019 | 4 | |
| 9 | Learning To Reach Goals Without Reinforcement Learning | 2019 | 3 |
| 10 | 2022 | 3 | |
| 11 | Datasets for Data-Driven Reinforcement Learning | 2020 | 2 |
| 12 | 2021 | 1 | |
| 13 | 1999 | 1 | |
| 14 | 2023 | 0 |
About Justin Fu
Justin Fu is a scholar working on Artificial Intelligence, Automotive Engineering, Management Science and Operations Research, Electrical and Electronic Engineering and Biomedical Engineering, having authored 14 papers that have together received 145 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (7 papers), Autonomous Vehicle Technology and Safety (3 papers), Adversarial Robustness in Machine Learning (3 papers), Speech and dialogue systems (2 papers), AI in Service Interactions (2 papers), Topic Modeling (2 papers), Data Stream Mining Techniques (1 paper) and Antimicrobial Peptides and Activities (1 paper). The work is most often cited by research in Automotive Engineering (36 citations), Artificial Intelligence (96 citations), Computer Vision and Pattern Recognition (33 citations), Control and Systems Engineering (35 citations) and Management Science and Operations Research (13 citations). Justin Fu has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Sergey Levine, George Tucker, Aviral Kumar, Dragomir Anguelov, Shimon Whiteson, Yiren Lu, Sherry X. Yang, Siddharth Verma, Hongge Chen and Benjamin Sapp. Their work appears in journals such as Journal of Artificial Intelligence Research, Thin Solid Films, arXiv (Cornell University), 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.