Pei Shi
Impact in
- Water Science and Technology top 10%
- Water Quality Monitoring Technologies
-
- Water Quality Monitoring and Analysis
Papers in
-
- Machine Learning and ELM 3
- Advanced Technologies in Various Fields 2
-
- Water Quality Monitoring Technologies 5
- Co-authors
- Guanghui Li (5 shared papers)Guangyan Huang (3 shared papers)Chi Chen (4 shared papers)Dan Sun (4 shared papers)Tianran Yan (2 shared papers)Liang Zhang (2 shared papers)Hongtai Li (2 shared papers)Tong Guo (2 shared papers)
- Journals
- Sensors (2 papers)IEEE Access (2 papers)IEEE Transactions on Instrumentation and Measurement (1 paper)Applied Sciences (1 paper)Forests (1 paper)
- Partner nations
- ChinaAustraliaUnited States
In The Last Decade
Pei Shi
16 papers receiving 301 citations
Peers
Comparison fields: 5 of 64
- Water Science and Technology 91
- Industrial and Manufacturing Engineering 29
- Environmental Engineering 48
- Electrical and Electronic Engineering 121
- Nature and Landscape Conservation 20
Countries citing papers authored by Pei Shi
This map shows the geographic impact of Pei 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 Pei Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pei Shi more than expected).
Fields of papers citing papers by Pei Shi
This network shows the impact of papers produced by Pei 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 Pei Shi. The network helps show where Pei Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Pei Shi, 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 | 2022 | 102 | |
| 2 | 2019 | 60 | |
| 3 | 2020 | 33 | |
| 4 | 2018 | 14 | |
| 5 | 2024 | 14 | |
| 6 | 2021 | 14 | |
| 7 | 2022 | 12 | |
| 8 | 2023 | 12 | |
| 9 | 2013 | 10 | |
| 10 | 2023 | 8 | |
| 11 | 2024 | 6 | |
| 12 | 2019 | 5 | |
| 13 | 2024 | 4 | |
| 14 | 2011 | 4 | |
| 15 | 2025 | 2 | |
| 16 | 2025 | 1 |
About Pei Shi
Pei Shi is a scholar working on Artificial Intelligence, Water Science and Technology, Electrical and Electronic Engineering, Global and Planetary Change and Materials Chemistry, having authored 16 papers that have together received 301 indexed citations. Recurring topics across this work include Water Quality Monitoring Technologies (5 papers), Advanced Battery Materials and Technologies (4 papers), Advancements in Battery Materials (4 papers), Machine Learning and ELM (3 papers), Surface Roughness and Optical Measurements (2 papers), Advanced Technologies in Various Fields (2 papers), Hydrological Forecasting Using AI (2 papers) and Water Quality Monitoring and Analysis (2 papers). The work is most often cited by research in Water Science and Technology (91 citations), Industrial and Manufacturing Engineering (29 citations), Environmental Engineering (48 citations), Electrical and Electronic Engineering (121 citations) and Nature and Landscape Conservation (20 citations). Pei Shi has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Guanghui Li, Guangyan Huang, Chi Chen, Dan Sun, Tianran Yan, Liang Zhang, Hongtai Li, Tong Guo, Xiao Xia and Jing Mao. Their work appears in journals such as Sensors, IEEE Access, IEEE Transactions on Instrumentation and Measurement, Applied Sciences and Forests.
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.