Gao Jun
Impact in
- Automotive Engineering top 5%
- Autonomous Vehicle Technology and Safety
-
- Traffic and Road Safety
Papers in
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- Autonomous Vehicle Technology and Safety 14
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- Video Surveillance and Tracking Methods 6
- Advanced Neural Network Applications 4
- Co-authors
- Yi Lu Murphey (15 shared papers)Saeed Zahedi (1 shared paper)David Moser (1 shared paper)Liudi Jiang (1 shared paper)Michael McGrath (1 shared paper)Dan L. Bader (1 shared paper)Jinghua Tang (1 shared paper)Man Deng (2 shared papers)
- Journals
- Machine Vision and Applications (2 papers)Separation and Purification Technology (2 papers)Computing (1 paper)International Journal of Automotive Technology (1 paper)Frontiers in Psychology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Gao Jun
42 papers receiving 356 citations
Hit Papers
Peers
Comparison fields: 5 of 78
- Automotive Engineering 125
- Safety, Risk, Reliability and Quality 53
- Building and Construction 46
- Computer Vision and Pattern Recognition 62
- Renewable Energy, Sustainability and the Environment 46
Countries citing papers authored by Gao Jun
This map shows the geographic impact of Gao Jun'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 Gao Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gao Jun more than expected).
Fields of papers citing papers by Gao Jun
This network shows the impact of papers produced by Gao Jun. 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 Gao Jun. The network helps show where Gao Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Gao Jun, 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 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 65 | |
| 2 | 2016 | 61 | |
| 3 | Rational design of a novel MIL-100(Fe)/TpPa-1 COF direct Z-scheme heterojunction for photo-self-Fenton removal of antibiotics: Performance and ecotoxicity assessment Hit paper breakdown → | 2025 | 44 |
| 4 | 2019 | 24 | |
| 5 | 2020 | 22 | |
| 6 | 2025 | 21 | |
| 7 | 2019 | 11 | |
| 8 | 2016 | 9 | |
| 9 | 2023 | 9 | |
| 10 | 2022 | 8 | |
| 11 | 2020 | 8 | |
| 12 | 2021 | 7 | |
| 13 | 2025 | 5 | |
| 14 | 2020 | 5 | |
| 15 | 2022 | 5 | |
| 16 | 2011 | 5 | |
| 17 | 2019 | 5 | |
| 18 | 2018 | 4 | |
| 19 | 2023 | 4 | |
| 20 | 2008 | 4 |
About Gao Jun
Gao Jun is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Building and Construction and Electrical and Electronic Engineering, having authored 52 papers that have together received 361 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (14 papers), Traffic Prediction and Management Techniques (8 papers), Video Surveillance and Tracking Methods (6 papers), Anomaly Detection Techniques and Applications (5 papers), Advanced Neural Network Applications (4 papers), Traffic and Road Safety (3 papers), Covalent Organic Framework Applications (3 papers) and Optimization and Packing Problems (2 papers). The work is most often cited by research in Automotive Engineering (125 citations), Safety, Risk, Reliability and Quality (53 citations), Building and Construction (46 citations), Computer Vision and Pattern Recognition (62 citations) and Renewable Energy, Sustainability and the Environment (46 citations). Gao Jun has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yi Lu Murphey, Saeed Zahedi, David Moser, Liudi Jiang, Michael McGrath, Dan L. Bader, Jinghua Tang, Man Deng, Qi Wang and Erpeng Wang. Their work appears in journals such as Machine Vision and Applications, Separation and Purification Technology, Computing, International Journal of Automotive Technology and Frontiers in Psychology.
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.