Xiaosong Jia
- Automotive Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Building and Construction top 10%
- Control and Systems Engineering top 10%
- Co-authors
- Hongyang LiLi ChenJunchi YanXizhou ZhuYu QiaoQiang LiuYihan HuTianwei Lin
- Topics
- Autonomous Vehicle Technology and Safety (8 papers)Advanced Neural Network Applications (4 papers)Reinforcement Learning in Robotics (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionIEEE Transactions on Knowledge and Data Engineering
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xiaosong Jia
10 papers receiving 530 citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Automotive Engineering 268
- Computer Vision and Pattern Recognition 263
- Artificial Intelligence 151
- Building and Construction 69
- Control and Systems Engineering 68
Countries citing papers authored by Xiaosong Jia
This map shows the geographic impact of Xiaosong Jia'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 Xiaosong Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaosong Jia more than expected).
Fields of papers citing papers by Xiaosong Jia
This network shows the impact of papers produced by Xiaosong Jia. 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 Xiaosong Jia. The network helps show where Xiaosong Jia may publish in the future.
Co-authorship network of co-authors of Xiaosong Jia
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaosong Jia. A scholar is included among the top collaborators of Xiaosong Jia based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiaosong Jia. Xiaosong Jia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | Planning-oriented Autonomous Drivingbreakdown → | 349 |
| 5 | 90 | |
| 6 | 42 | |
| 7 | 22 | |
| 8 | 1 | |
| 9 | Multi-Agent Trajectory Prediction by Combining Egocentric and Allocentric Views | 10 |
| 10 | 20 | |
| 11 | 4 |
About Xiaosong Jia
Xiaosong Jia is a scholar working on Automotive Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 11 papers that have together received 544 indexed citations. Recurring topics across this work include Autonomous Vehicle Technology and Safety (8 papers), Advanced Neural Network Applications (4 papers) and Reinforcement Learning in Robotics (3 papers). The work is most often cited by research in Automotive Engineering (268 citations), Computer Vision and Pattern Recognition (263 citations) and Building and Construction (69 citations). Xiaosong Jia has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Hongyang Li, Li Chen, Junchi Yan, Xizhou Zhu, Yu Qiao, Qiang Liu, Yihan Hu, Tianwei Lin, Keyu Li and Chonghao Sima. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and IEEE Transactions on Knowledge and Data Engineering.
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.