Qin Shi
- Renewable Energy, Sustainability and the Environment top 5%
- Materials Chemistry
- Electrical and Electronic Engineering
- Water Science and Technology top 10%
- Artificial Intelligence top 10%
- Co-authors
- Hui WangZhaoyong BianXiaozhe SongShaolei LiuPengyi TangTeresa AndreuJ.R. MoranteSebastián Murcia‐López
- Topics
- Speech Recognition and Synthesis (14 papers)Natural Language Processing Techniques (10 papers)Advanced Photocatalysis Techniques (7 papers)
- Cited by
- Renewable Energy, Sustainability and the EnvironmentElectrochemistryWater Science and Technology
- Journals
- SHILAP Revista de lepidopterologíaAdvanced Energy MaterialsJournal of The Electrochemical Society
- Partner nations
- ChinaUnited StatesSpain
In The Last Decade
Qin Shi
47 papers receiving 760 citations
Peers
Comparison fields: 5 of 78
- Renewable Energy, Sustainability and the Environment 437
- Materials Chemistry 299
- Electrical and Electronic Engineering 226
- Water Science and Technology 117
- Artificial Intelligence 104
Countries citing papers authored by Qin Shi
This map shows the geographic impact of Qin Shi'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 Qin Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qin Shi more than expected).
Fields of papers citing papers by Qin Shi
This network shows the impact of papers produced by Qin Shi. 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 Qin Shi. The network helps show where Qin Shi may publish in the future.
Co-authorship network of co-authors of Qin Shi
This figure shows the co-authorship network connecting the top 25 collaborators of Qin Shi. A scholar is included among the top collaborators of Qin Shi 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 Qin Shi. Qin Shi 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 | 32 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 8 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 97 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 14 | |
| 15 | 177 | |
| 16 | 18 | |
| 17 | 19 | |
| 18 | 3 | |
| 19 | 15 | |
| 20 | 8 |
About Qin Shi
Qin Shi is a scholar working on Process Chemistry and Technology, Renewable Energy, Sustainability and the Environment and Artificial Intelligence, having authored 52 papers that have together received 796 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (14 papers), Natural Language Processing Techniques (10 papers) and Advanced Photocatalysis Techniques (7 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (437 citations), Electrochemistry (79 citations) and Water Science and Technology (117 citations). Qin Shi has collaborated with scholars based in China, United States and Spain. Frequent co-authors include Hui Wang, Zhaoyong Bian, Xiaozhe Song, Shaolei Liu, Pengyi Tang, Teresa Andreu, J.R. Morante, Sebastián Murcia‐López, Cristina Flox and Meng Zhang. Their work appears in journals such as SHILAP Revista de lepidopterología, Advanced Energy Materials and Journal of The Electrochemical Society.
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.