Yangang Ren
- Control and Systems Engineering top 10%
- Automotive Engineering top 5%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics top 10%
- Topics
- Autonomous Vehicle Technology and Safety (10 papers)Traffic control and management (9 papers)Reinforcement Learning in Robotics (9 papers)
- Journals
- IEEE Transactions on Intelligent Transportation SystemsIEEE Transactions on Neural Networks and Learning SystemsNeurocomputing
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Yangang Ren
13 papers receiving 310 citations
Peers
Comparison fields: 5 of 45
- Control and Systems Engineering 138
- Automotive Engineering 133
- Artificial Intelligence 128
- Computer Vision and Pattern Recognition 47
- Computational Theory and Mathematics 37
Countries citing papers authored by Yangang Ren
This map shows the geographic impact of Yangang Ren'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 Yangang Ren with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yangang Ren more than expected).
Fields of papers citing papers by Yangang Ren
This network shows the impact of papers produced by Yangang Ren. 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 Yangang Ren. The network helps show where Yangang Ren may publish in the future.
Co-authorship network of co-authors of Yangang Ren
This figure shows the co-authorship network connecting the top 25 collaborators of Yangang Ren. A scholar is included among the top collaborators of Yangang Ren 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 Yangang Ren. Yangang Ren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 11 | |
| 4 | 9 | |
| 5 | 8 | |
| 6 | 0 | |
| 7 | 31 | |
| 8 | 30 | |
| 9 | 16 | |
| 10 | 164 | |
| 11 | 7 | |
| 12 | 6 | |
| 13 | Addressing Value Estimation Errors in Reinforcement Learning with a State-Action Return Distribution Function | 1 |
| 14 | 22 | |
| 15 | Centralized Conflict-free Cooperation for Connected and Automated Vehicles at Intersections by Proximal Policy Optimization. | 2 |
About Yangang Ren
Yangang Ren is a scholar working on Automotive Engineering, Control and Systems Engineering and Artificial Intelligence, having authored 15 papers that have together received 323 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (10 papers), Traffic control and management (9 papers) and Reinforcement Learning in Robotics (9 papers). The work is most often cited by research in Automotive Engineering (133 citations), Control and Systems Engineering (138 citations) and Artificial Intelligence (128 citations). Yangang Ren has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Shengbo Eben Li, Yang Guan, Jingliang Duan, Qi Sun, Bo Cheng, Renjie Li, Wenjun Wang, Qingkun Li, Ziyu Lin and Sifa Zheng. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.
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.