Han Shi
Impact in
-
- Face and Expression Recognition
- Face recognition and analysis
-
- Energy and Environment Impacts
Papers in
-
- Topic Modeling 10
- Natural Language Processing Techniques 6
- Co-authors
- Dongmei Zhang (8 shared papers)Bo Wang (8 shared papers)Hai Zhao (1 shared paper)Gang Pan (1 shared paper)Yueming Wang (1 shared paper)Nana Deng (8 shared papers)Zhaohua Wang (6 shared papers)Yueming Qiu (6 shared papers)
- Journals
- Nature Communications (3 papers)Chemical Communications (2 papers)IEEE Access (2 papers)Cold Regions Science and Technology (2 papers)Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Han Shi
66 papers receiving 481 citations
Peers
Comparison fields: 5 of 112
- Computer Vision and Pattern Recognition 70
- Pollution 38
- Renewable Energy, Sustainability and the Environment 52
- Signal Processing 32
- Artificial Intelligence 90
Countries citing papers authored by Han Shi
This map shows the geographic impact of Han 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 Han Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Han Shi more than expected).
Fields of papers citing papers by Han Shi
This network shows the impact of papers produced by Han 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 Han Shi. The network helps show where Han Shi may publish in the future.
Co-authors
The 25 scholars most cited alongside Han 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
Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 42 | |
| 2 | 2023 | 37 | |
| 3 | 2024 | 31 | |
| 4 | 2023 | 31 | |
| 5 | 2022 | 25 | |
| 6 | 2023 | 21 | |
| 7 | 2023 | 19 | |
| 8 | 2024 | 18 | |
| 9 | 2023 | 17 | |
| 10 | 2023 | 16 | |
| 11 | 2025 | 14 | |
| 12 | 2023 | 13 | |
| 13 | 2025 | 11 | |
| 14 | 2022 | 11 | |
| 15 | 2017 | 9 | |
| 16 | 2019 | 9 | |
| 17 | 2024 | 8 | |
| 18 | 2022 | 8 | |
| 19 | 2022 | 8 | |
| 20 | 2022 | 8 |
About Han Shi
Han Shi is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 78 papers that have together received 495 indexed citations. Recurring topics across this work include Topic Modeling (10 papers), Natural Language Processing Techniques (6 papers), Icing and De-icing Technologies (5 papers), Energy and Environment Impacts (5 papers), Energy, Environment, and Transportation Policies (4 papers), Electrocatalysts for Energy Conversion (3 papers), Advanced Photocatalysis Techniques (2 papers) and Metal-Organic Frameworks: Synthesis and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (70 citations), Pollution (38 citations), Renewable Energy, Sustainability and the Environment (52 citations), Signal Processing (32 citations) and Artificial Intelligence (90 citations). Han Shi has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Dongmei Zhang, Bo Wang, Hai Zhao, Gang Pan, Yueming Wang, Nana Deng, Zhaohua Wang, Yueming Qiu, Pingchuan Ma and Shuai Wang. Their work appears in journals such as Nature Communications, Chemical Communications, IEEE Access, Cold Regions Science and Technology and Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy.
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.