Ning Gui
Impact in
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- Context-Aware Activity Recognition Systems
- Face and Expression Recognition
- Demography top 5%
- Technology Use by Older Adults
Papers in
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- Advanced Software Engineering Methodologies 13
- Advanced Graph Neural Networks 9
- Machine Learning and Data Classification 3
- Privacy-Preserving Technologies in Data 3
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- Face and Expression Recognition 4
- Context-Aware Activity Recognition Systems 3
- Co-authors
- Vincenzo De Florio (18 shared papers)Chris L. Blondia (16 shared papers)Hong Sun (13 shared papers)Geert Deconinck (9 shared papers)Zhifeng Qiu (13 shared papers)Weihua Gui (5 shared papers)Yun Wang (1 shared paper)Junbo Liu (1 shared paper)
In The Last Decade
Ning Gui
47 papers receiving 699 citations
Peers
Comparison fields: 5 of 69
- Computer Vision and Pattern Recognition 171
- Demography 79
- Artificial Intelligence 233
- Building and Construction 70
- Health Information Management 27
Countries citing papers authored by Ning Gui
This map shows the geographic impact of Ning Gui'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 Ning Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Gui more than expected).
Fields of papers citing papers by Ning Gui
This network shows the impact of papers produced by Ning Gui. 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 Ning Gui. The network helps show where Ning Gui may publish in the future.
Co-authors
The 25 scholars most cited alongside Ning Gui, 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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 186 | |
| 2 | 2019 | 58 | |
| 3 | 2021 | 50 | |
| 4 | 2010 | 38 | |
| 5 | 2017 | 38 | |
| 6 | 2018 | 33 | |
| 7 | 2010 | 20 | |
| 8 | 2019 | 20 | |
| 9 | 2007 | 19 | |
| 10 | 2008 | 18 | |
| 11 | 2023 | 18 | |
| 12 | 2022 | 14 | |
| 13 | 2009 | 13 | |
| 14 | 2023 | 13 | |
| 15 | 2024 | 13 | |
| 16 | 2008 | 12 | |
| 17 | 2022 | 12 | |
| 18 | 2012 | 11 | |
| 19 | 2008 | 10 | |
| 20 | 2012 | 10 |
About Ning Gui
Ning Gui is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Building and Construction, Software and Health Information Management, having authored 56 papers that have together received 732 indexed citations. Recurring topics across this work include Advanced Software Engineering Methodologies (13 papers), Advanced Graph Neural Networks (9 papers), BIM and Construction Integration (4 papers), Face and Expression Recognition (4 papers), Electric Power System Optimization (3 papers), Machine Learning and Data Classification (3 papers), Context-Aware Activity Recognition Systems (3 papers) and Privacy-Preserving Technologies in Data (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (171 citations), Demography (79 citations), Artificial Intelligence (233 citations), Building and Construction (70 citations) and Health Information Management (27 citations). Ning Gui has collaborated with scholars based in China, Belgium and Singapore. Frequent co-authors include Vincenzo De Florio, Chris L. Blondia, Hong Sun, Geert Deconinck, Zhifeng Qiu, Weihua Gui, Yun Wang, Junbo Liu, Lingxiang Huang and Young Hoon Joo. Their work appears in journals such as Knowledge-Based Systems, IEEE Transactions on Knowledge and Data Engineering, International Journal of Electrical Power & Energy Systems, ACM Transactions on Knowledge Discovery from Data and Journal of Systems and Software.
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.