Qingpeng Cai
- Artificial Intelligence top 10%
- Information Systems top 5%
- Management Science and Operations Research top 5%
- Transportation top 5%
- Automotive Engineering top 10%
- Co-authors
- Pingzhong TangAris Filos-RatsikasLongbo HuangZhixuan FangWenqiao ZhangYiwei ZhangShengyu ZhangShuchang Liu
- Topics
- Recommender Systems and Techniques (12 papers)Advanced Bandit Algorithms Research (10 papers)Reinforcement Learning in Robotics (9 papers)
In The Last Decade
Qingpeng Cai
31 papers receiving 422 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 155
- Information Systems 114
- Management Science and Operations Research 104
- Transportation 89
- Automotive Engineering 82
Countries citing papers authored by Qingpeng Cai
This map shows the geographic impact of Qingpeng Cai'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 Qingpeng Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingpeng Cai more than expected).
Fields of papers citing papers by Qingpeng Cai
This network shows the impact of papers produced by Qingpeng Cai. 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 Qingpeng Cai. The network helps show where Qingpeng Cai may publish in the future.
Co-authorship network of co-authors of Qingpeng Cai
This figure shows the co-authorship network connecting the top 25 collaborators of Qingpeng Cai. A scholar is included among the top collaborators of Qingpeng Cai 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 Qingpeng Cai. Qingpeng Cai 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 | 1 | |
| 4 | 1 | |
| 5 | 12 | |
| 6 | 1 | |
| 7 | 15 | |
| 8 | 23 | |
| 9 | 22 | |
| 10 | 11 | |
| 11 | 8 | |
| 12 | 7 | |
| 13 | 1 | |
| 14 | 1 | |
| 15 | Softmax Deep Double Deterministic Policy Gradients | 1 |
| 16 | Generalized deterministic policy gradient algorithms. | 1 |
| 17 | Policy Gradients for Contextual Bandits. | 1 |
| 18 | 1 | |
| 19 | 1 | |
| 20 | Facility location with minimax envy | 16 |
About Qingpeng Cai
Qingpeng Cai is a scholar working on Management Science and Operations Research, Information Systems and Transportation, having authored 33 papers that have together received 437 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (12 papers), Advanced Bandit Algorithms Research (10 papers) and Reinforcement Learning in Robotics (9 papers). The work is most often cited by research in Transportation (89 citations), Management Science and Operations Research (104 citations) and Automotive Engineering (82 citations). Qingpeng Cai has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Pingzhong Tang, Aris Filos-Ratsikas, Longbo Huang, Zhixuan Fang, Wenqiao Zhang, Yiwei Zhang, Shengyu Zhang, Shuchang Liu, Peng Jiang and Andrew Makmur. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Proceedings of the VLDB Endowment and Autonomous Agents and Multi-Agent Systems.
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.