Tianren Zhang
- Electrical and Electronic Engineering
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Automotive Engineering
- Control and Systems Engineering
- Topics
- Reinforcement Learning in Robotics (5 papers)Electric Vehicles and Infrastructure (3 papers)Human Pose and Action Recognition (3 papers)
- Cited by
- Energy Engineering and Power TechnologyAutomotive EngineeringComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceApplied EnergyRenewable Energy
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Tianren Zhang
15 papers receiving 275 citations
Peers
Comparison fields: 5 of 60
- Electrical and Electronic Engineering 151
- Artificial Intelligence 68
- Computer Vision and Pattern Recognition 57
- Automotive Engineering 40
- Control and Systems Engineering 36
Countries citing papers authored by Tianren Zhang
This map shows the geographic impact of Tianren Zhang'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 Tianren Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianren Zhang more than expected).
Fields of papers citing papers by Tianren Zhang
This network shows the impact of papers produced by Tianren Zhang. 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 Tianren Zhang. The network helps show where Tianren Zhang may publish in the future.
Co-authorship network of co-authors of Tianren Zhang
This figure shows the co-authorship network connecting the top 25 collaborators of Tianren Zhang. A scholar is included among the top collaborators of Tianren Zhang 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 Tianren Zhang. Tianren Zhang 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 | 2 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 4 | |
| 6 | 3 | |
| 7 | 66 | |
| 8 | 1 | |
| 9 | 18 | |
| 10 | 2 | |
| 11 | 9 | |
| 12 | 4 | |
| 13 | Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning. | 1 |
| 14 | 111 | |
| 15 | 45 |
About Tianren Zhang
Tianren Zhang is a scholar working on Automotive Engineering, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 15 papers that have together received 282 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Electric Vehicles and Infrastructure (3 papers) and Human Pose and Action Recognition (3 papers). The work is most often cited by research in Energy Engineering and Power Technology (16 citations), Automotive Engineering (40 citations) and Computer Vision and Pattern Recognition (57 citations). Tianren Zhang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Bo Gu, Hang Meng, Jinhua Zhang, Yuping Huang, Jiwen Lu, Jie Zhou, Guangyi Chen, Feng Chen, Tian Tan and Weijia Yang. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Applied Energy and Renewable Energy.
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.