Shaojun Gan
Impact in
- Ocean Engineering top 5%
- Maritime Navigation and Safety
- Ship Hydrodynamics and Maneuverability
-
- Maritime Ports and Logistics
Papers in
-
- Neural Networks and Applications 4
-
- Maritime Navigation and Safety 6
- Co-authors
- Tingli Cheng (5 shared papers)Shan Liang (8 shared papers)Kang Li (6 shared papers)Jing Deng (3 shared papers)Yanxia Wang (8 shared papers)Kang Li (4 shared papers)P.J. Fleming (2 shared papers)Zhile Yang (2 shared papers)
- Journals
- IEEE Transactions on Intelligent Transportation Systems (2 papers)Energy (2 papers)Ocean Engineering (2 papers)Transportation Research Part D Transport and Environment (1 paper)Energy & Environment (1 paper)
- Partner nations
- ChinaUnited KingdomSaudi Arabia
In The Last Decade
Shaojun Gan
23 papers receiving 339 citations
Peers
Comparison fields: 5 of 66
- Ocean Engineering 97
- Industrial and Manufacturing Engineering 50
- Environmental Engineering 52
- Transportation 22
- Artificial Intelligence 89
Countries citing papers authored by Shaojun Gan
This map shows the geographic impact of Shaojun Gan'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 Shaojun Gan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shaojun Gan more than expected).
Fields of papers citing papers by Shaojun Gan
This network shows the impact of papers produced by Shaojun Gan. 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 Shaojun Gan. The network helps show where Shaojun Gan may publish in the future.
Co-authors
The 25 scholars most cited alongside Shaojun Gan, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 52 | |
| 2 | 2016 | 46 | |
| 3 | 2016 | 42 | |
| 4 | 2020 | 29 | |
| 5 | 2017 | 24 | |
| 6 | 2023 | 22 | |
| 7 | 2019 | 19 | |
| 8 | 2019 | 18 | |
| 9 | 2022 | 16 | |
| 10 | 2016 | 12 | |
| 11 | 2020 | 11 | |
| 12 | 2018 | 11 | |
| 13 | 2023 | 10 | |
| 14 | 2021 | 9 | |
| 15 | 2014 | 4 | |
| 16 | 2016 | 4 | |
| 17 | 2019 | 4 | |
| 18 | 2016 | 3 | |
| 19 | 2025 | 2 | |
| 20 | 2024 | 1 |
About Shaojun Gan
Shaojun Gan is a scholar working on Artificial Intelligence, Ocean Engineering, Building and Construction, Industrial and Manufacturing Engineering and Automotive Engineering, having authored 25 papers that have together received 342 indexed citations. Recurring topics across this work include Maritime Navigation and Safety (6 papers), Transportation and Mobility Innovations (4 papers), Transportation Planning and Optimization (4 papers), Traffic Prediction and Management Techniques (4 papers), Neural Networks and Applications (4 papers), Electric Vehicles and Infrastructure (3 papers), Energy Load and Power Forecasting (2 papers) and Blind Source Separation Techniques (2 papers). The work is most often cited by research in Ocean Engineering (97 citations), Industrial and Manufacturing Engineering (50 citations), Environmental Engineering (52 citations), Transportation (22 citations) and Artificial Intelligence (89 citations). Shaojun Gan has collaborated with scholars based in China, United Kingdom and Saudi Arabia. Frequent co-authors include Tingli Cheng, Shan Liang, Kang Li, Jing Deng, Yanxia Wang, Kang Li, P.J. Fleming, Zhile Yang, Minyou Chen and Kang Li. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, Energy, Ocean Engineering, Transportation Research Part D Transport and Environment and Energy & Environment.
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.