Jingwei Ji
Impact in
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- Human Pose and Action Recognition
- Multimodal Machine Learning Applications
- Video Analysis and Summarization
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- Fire dynamics and safety research
Papers in
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- Fire dynamics and safety research 11
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- Evacuation and Crowd Dynamics 10
- Co-authors
- Juan Carlos Niebles (3 shared papers)Ranjay Krishna (1 shared paper)Li Fei-Fei (1 shared paper)Kaidi Cao (2 shared papers)Alain Puisieux (2 shared papers)Mehmet Öztürk (2 shared papers)Chien-Yi Chang (1 shared paper)Zhangjie Cao (1 shared paper)
- Journals
- Journal of Fire Sciences (3 papers)ACS Applied Materials & Interfaces (2 papers)Fire (2 papers)Endocrinology (2 papers)Chinese Optics Letters (2 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Jingwei Ji
59 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 133
- Computer Vision and Pattern Recognition 346
- Safety, Risk, Reliability and Quality 116
- Reproductive Medicine 74
- Artificial Intelligence 220
- Ocean Engineering 81
Countries citing papers authored by Jingwei Ji
This map shows the geographic impact of Jingwei Ji'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 Jingwei Ji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingwei Ji more than expected).
Fields of papers citing papers by Jingwei Ji
This network shows the impact of papers produced by Jingwei Ji. 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 Jingwei Ji. The network helps show where Jingwei Ji may publish in the future.
Co-authors
The 25 scholars most cited alongside Jingwei Ji, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 165 | |
| 2 | 2020 | 153 | |
| 3 | 1993 | 114 | |
| 4 | 2000 | 100 | |
| 5 | 1996 | 71 | |
| 6 | 2021 | 65 | |
| 7 | 1993 | 39 | |
| 8 | 2018 | 35 | |
| 9 | 1999 | 29 | |
| 10 | 2019 | 27 | |
| 11 | 2006 | 26 | |
| 12 | 2017 | 23 | |
| 13 | 2020 | 23 | |
| 14 | 2021 | 16 | |
| 15 | 2023 | 13 | |
| 16 | 2016 | 13 | |
| 17 | 2017 | 13 | |
| 18 | 2023 | 12 | |
| 19 | 2005 | 12 | |
| 20 | 2023 | 11 |
About Jingwei Ji
Jingwei Ji is a scholar working on Safety, Risk, Reliability and Quality, Ocean Engineering, Materials Chemistry, Computer Vision and Pattern Recognition and Global and Planetary Change, having authored 61 papers that have together received 1.1k indexed citations. Recurring topics across this work include Fire dynamics and safety research (11 papers), Evacuation and Crowd Dynamics (10 papers), Human Pose and Action Recognition (6 papers), Fire effects on ecosystems (5 papers), Multimodal Machine Learning Applications (5 papers), Advanced Frequency and Time Standards (5 papers), Combustion and Detonation Processes (4 papers) and Atomic and Subatomic Physics Research (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (346 citations), Safety, Risk, Reliability and Quality (116 citations), Reproductive Medicine (74 citations), Artificial Intelligence (220 citations) and Ocean Engineering (81 citations). Jingwei Ji has collaborated with scholars based in China, United States and France. Frequent co-authors include Juan Carlos Niebles, Ranjay Krishna, Li Fei-Fei, Kaidi Cao, Alain Puisieux, Mehmet Öztürk, Chien-Yi Chang, Zhangjie Cao, Mohamed Benahmed and Éric Tabone. Their work appears in journals such as Journal of Fire Sciences, ACS Applied Materials & Interfaces, Fire, Endocrinology and Chinese Optics Letters.
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.