Yali Du
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics 13
- Adversarial Robustness in Machine Learning 5
- Artificial Intelligence in Games 4
- Topic Modeling 3
- Data Stream Mining Techniques 3
- Automotive Engineering top 10%
- Control and Systems Engineering top 10%
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- Distributed Control Multi-Agent Systems 3
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- Adaptive Dynamic Programming Control 3
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- Recommender Systems and Techniques 3
- Co-authors
- Meng FangLei HanAlois KnollShangding GuChengqi ZhangYang LongLing ChenJun Wang
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Artificial Intelligence (1 paper)IEEE Transactions on Cybernetics (1 paper)
- Partner nations
- United KingdomChinaAustralia
In The Last Decade
Yali Du
30 papers receiving 497 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Artificial Intelligence 275
- Automotive Engineering 77
- Industrial and Manufacturing Engineering 59
- Computer Vision and Pattern Recognition 88
- Control and Systems Engineering 93
Countries citing papers authored by Yali Du
This map shows the geographic impact of Yali Du'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 Yali Du with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yali Du more than expected).
Fields of papers citing papers by Yali Du
This network shows the impact of papers produced by Yali Du. 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 Yali Du. The network helps show where Yali Du may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yali Du, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 15 | |
| 4 | 2024 | 1 | |
| 5 | A Review of Safe Reinforcement Learning: Methods, Theories, and Applicationsbreakdown → | 2024 | 66 |
| 6 | 2024 | 0 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 53 | |
| 11 | 2023 | 4 | |
| 12 | 2023 | 3 | |
| 13 | 2022 | 3 | |
| 14 | 2021 | 18 | |
| 15 | 2021 | 81 | |
| 16 | Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games | 2020 | 5 |
| 17 | LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning | 2019 | 45 |
| 18 | Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI. | 2019 | 16 |
| 19 | Curriculum-guided Hindsight Experience Replay | 2019 | 50 |
| 20 | 2019 | 0 |
About Yali Du
Yali Du is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 35 papers that have together received 516 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (13 papers), Adversarial Robustness in Machine Learning (5 papers), Artificial Intelligence in Games (4 papers), Topic Modeling (3 papers), Distributed Control Multi-Agent Systems (3 papers), Data Stream Mining Techniques (3 papers), Adaptive Dynamic Programming Control (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (275 citations), Automotive Engineering (77 citations) and Industrial and Manufacturing Engineering (59 citations). Yali Du has collaborated with scholars based in United Kingdom, China and Australia. Frequent co-authors include Meng Fang, Lei Han, Alois Knoll, Shangding Gu, Chengqi Zhang, Yang Long, Ling Chen, Jun Wang, Gangyan Xu and Dacheng Tao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Artificial Intelligence and IEEE Transactions on Cybernetics.
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.