Biao Qin
- Materials Chemistry top 10%
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Renewable Energy, Sustainability and the Environment top 10%
- Electronic, Optical and Magnetic Materials
- Topics
- 2D Materials and Applications (11 papers)Data Management and Algorithms (10 papers)Topic Modeling (7 papers)
- Cited by
- Materials ChemistryProcess Chemistry and TechnologyRenewable Energy, Sustainability and the Environment
- Journals
- Chemical ReviewsNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Biao Qin
64 papers receiving 933 citations
Peers
Comparison fields: 5 of 110
- Materials Chemistry 453
- Electrical and Electronic Engineering 307
- Artificial Intelligence 177
- Renewable Energy, Sustainability and the Environment 126
- Electronic, Optical and Magnetic Materials 126
Countries citing papers authored by Biao Qin
This map shows the geographic impact of Biao Qin'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 Biao Qin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Biao Qin more than expected).
Fields of papers citing papers by Biao Qin
This network shows the impact of papers produced by Biao Qin. 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 Biao Qin. The network helps show where Biao Qin may publish in the future.
Co-authorship network of co-authors of Biao Qin
This figure shows the co-authorship network connecting the top 25 collaborators of Biao Qin. A scholar is included among the top collaborators of Biao Qin 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 Biao Qin. Biao Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 13 | |
| 4 | 18 | |
| 5 | 1 | |
| 6 | 42 | |
| 7 | 4 | |
| 8 | 54 | |
| 9 | 37 | |
| 10 | 6 | |
| 11 | 124 | |
| 12 | 38 | |
| 13 | 12 | |
| 14 | 98 | |
| 15 | 1 | |
| 16 | Differential semantics of intervention in Bayesian networks | 1 |
| 17 | Belief-kinematics Jeffrey's rules in the theory of evidence | 1 |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 13 |
About Biao Qin
Biao Qin is a scholar working on Process Chemistry and Technology, Signal Processing and Artificial Intelligence, having authored 67 papers that have together received 986 indexed citations. Recurring topics across this work include 2D Materials and Applications (11 papers), Data Management and Algorithms (10 papers) and Topic Modeling (7 papers). The work is most often cited by research in Materials Chemistry (453 citations), Process Chemistry and Technology (23 citations) and Renewable Energy, Sustainability and the Environment (126 citations). Biao Qin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xidong Duan, Bo Li, Mongur Hossain, Yuni Xia, Sunil Prabhakar, Yi-Cheng Tu, Jinliang Lin, Huifang Ma, Xiaoyong Du and Qinglin Xia. Their work appears in journals such as Chemical Reviews, Nature Communications and SHILAP Revista de lepidopterología.
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.