Mingfei Sun
Impact in
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
- Artificial Intelligence top 10%
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
Papers in
-
- Artificial Intelligence in Games 3
- Reinforcement Learning in Robotics 3
-
- Luminescence Properties of Advanced Materials 3
- Layered Double Hydroxides Synthesis and Applications 2
- Co-authors
- Qiang Fu (2 shared papers)Peilin Zhao (2 shared papers)Lanxiao Huang (2 shared papers)Liang Wang (2 shared papers)Bei Shi (2 shared papers)Deheng Ye (2 shared papers)Tengfei Shi (2 shared papers)Wei Yang (2 shared papers)
- Journals
- Journal of Alloys and Compounds (2 papers)Theoretical and Applied Genetics (1 paper)steel research international (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Materials Science in Semiconductor Processing (1 paper)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Mingfei Sun
13 papers receiving 312 citations
Peers
Comparison fields: 5 of 59
- Computer Science Applications 30
- Artificial Intelligence 153
- Computer Vision and Pattern Recognition 48
- Signal Processing 24
- Transportation 13
Countries citing papers authored by Mingfei Sun
This map shows the geographic impact of Mingfei 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 Mingfei Sun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingfei Sun more than expected).
Fields of papers citing papers by Mingfei Sun
This network shows the impact of papers produced by Mingfei 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 Mingfei Sun. The network helps show where Mingfei Sun may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingfei Sun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 189 | |
| 2 | 2021 | 40 | |
| 3 | 2020 | 28 | |
| 4 | 2023 | 19 | |
| 5 | 2018 | 13 | |
| 6 | 2024 | 7 | |
| 7 | 2024 | 6 | |
| 8 | 2023 | 5 | |
| 9 | 2022 | 3 | |
| 10 | 2022 | 2 | |
| 11 | 2024 | 2 | |
| 12 | 2022 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2024 | 0 |
About Mingfei Sun
Mingfei Sun is a scholar working on Artificial Intelligence, Materials Chemistry, Mechanical Engineering, Electrical and Electronic Engineering and Renewable Energy, Sustainability and the Environment, having authored 14 papers that have together received 317 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (3 papers), Advanced Photocatalysis Techniques (3 papers), Reinforcement Learning in Robotics (3 papers), Luminescence Properties of Advanced Materials (3 papers), Metallurgical Processes and Thermodynamics (2 papers), Layered Double Hydroxides Synthesis and Applications (2 papers), Digital Games and Media (2 papers) and Power System Optimization and Stability (1 paper). The work is most often cited by research in Computer Science Applications (30 citations), Artificial Intelligence (153 citations), Computer Vision and Pattern Recognition (48 citations), Signal Processing (24 citations) and Transportation (13 citations). Mingfei Sun has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Qiang Fu, Peilin Zhao, Lanxiao Huang, Liang Wang, Bei Shi, Deheng Ye, Tengfei Shi, Wei Yang, Qingwei Guo and Hongsheng Yu. Their work appears in journals such as Journal of Alloys and Compounds, Theoretical and Applied Genetics, steel research international, IEEE Transactions on Neural Networks and Learning Systems and Materials Science in Semiconductor Processing.
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.