Yali Du
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Automotive Engineering top 10%
- Computer Networks and Communications top 10%
- Co-authors
- Meng FangLei HanAlois KnollShangding GuChengqi ZhangYang LongLing ChenJun Wang
- Topics
- Reinforcement Learning in Robotics (13 papers)Adversarial Robustness in Machine Learning (5 papers)Artificial Intelligence in Games (4 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceArtificial IntelligenceIEEE Transactions on Cybernetics
- 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
- Control and Systems Engineering 93
- Computer Vision and Pattern Recognition 88
- Automotive Engineering 77
- Computer Networks and Communications 61
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 of co-authors of Yali Du
This figure shows the co-authorship network connecting the top 25 collaborators of Yali Du. A scholar is included among the top collaborators of Yali Du based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yali Du. Yali Du is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 15 | |
| 4 | 1 | |
| 5 | A Review of Safe Reinforcement Learning: Methods, Theories, and Applicationsbreakdown → | 66 |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 4 | |
| 9 | 0 | |
| 10 | 53 | |
| 11 | 4 | |
| 12 | 3 | |
| 13 | 3 | |
| 14 | 18 | |
| 15 | 81 | |
| 16 | Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games | 5 |
| 17 | LIIR: Learning Individual Intrinsic Reward in Multi-Agent Reinforcement Learning | 45 |
| 18 | Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI. | 16 |
| 19 | Curriculum-guided Hindsight Experience Replay | 50 |
| 20 | 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) and Artificial Intelligence in Games (4 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.