Chuangchuang Sun
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications
- Computational Theory and Mathematics top 10%
- Co-authors
- Ran DaiJianbin DuJonathan P. HowChristos G. CassandrasKyriakos G. VamvoudakisDong Ki KimMehran MesbahiJing Guo
- Topics
- Sparse and Compressive Sensing Techniques (8 papers)Reinforcement Learning in Robotics (8 papers)Advanced Optimization Algorithms Research (5 papers)
- Partner nations
- United StatesChina
In The Last Decade
Chuangchuang Sun
34 papers receiving 297 citations
Peers
Comparison fields: 5 of 49
- Aerospace Engineering 100
- Control and Systems Engineering 78
- Computer Vision and Pattern Recognition 75
- Computer Networks and Communications 56
- Computational Theory and Mathematics 50
Countries citing papers authored by Chuangchuang Sun
This map shows the geographic impact of Chuangchuang Sun'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 Chuangchuang Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chuangchuang Sun more than expected).
Fields of papers citing papers by Chuangchuang Sun
This network shows the impact of papers produced by Chuangchuang Sun. 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 Chuangchuang Sun. The network helps show where Chuangchuang Sun may publish in the future.
Co-authorship network of co-authors of Chuangchuang Sun
This figure shows the co-authorship network connecting the top 25 collaborators of Chuangchuang Sun. A scholar is included among the top collaborators of Chuangchuang Sun 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 Chuangchuang Sun. Chuangchuang Sun 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 | 1 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 1 | |
| 9 | 6 | |
| 10 | A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning | 1 |
| 11 | 4 | |
| 12 | 7 | |
| 13 | 5 | |
| 14 | 13 | |
| 15 | 5 | |
| 16 | 11 | |
| 17 | 8 | |
| 18 | 42 | |
| 19 | 5 | |
| 20 | 21 |
About Chuangchuang Sun
Chuangchuang Sun is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Statistics, Probability and Uncertainty, having authored 34 papers that have together received 303 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (8 papers), Reinforcement Learning in Robotics (8 papers) and Advanced Optimization Algorithms Research (5 papers). The work is most often cited by research in Numerical Analysis (28 citations), Aerospace Engineering (100 citations) and Computer Vision and Pattern Recognition (75 citations). Chuangchuang Sun has collaborated with scholars based in United States and China. Frequent co-authors include Ran Dai, Jianbin Du, Jonathan P. How, Christos G. Cassandras, Kyriakos G. Vamvoudakis, Dong Ki Kim, Mehran Mesbahi, Jing Guo, Ping Lu and Xiao Li. Their work appears in journals such as Automatica, Mechanical Systems and Signal Processing and IEEE Transactions on Robotics.
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.