Haojia Li
- Aerospace Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 10%
- Control and Systems Engineering top 10%
- Artificial Intelligence
- Co-authors
- Fei GaoChao XuYuman GaoXin ZhouHaojian LuQianhao WangTiankai YangXiangyong Wen
- Topics
- Robotics and Sensor-Based Localization (6 papers)Robotic Path Planning Algorithms (5 papers)Advanced Image and Video Retrieval Techniques (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionAerospace EngineeringComputer Networks and Communications
- Journals
- IEEE Transactions on RoboticsIEEE Transactions on Instrumentation and MeasurementScience Robotics
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Haojia Li
8 papers receiving 405 citations
Hit Papers
Peers
Comparison fields: 5 of 61
- Aerospace Engineering 217
- Computer Vision and Pattern Recognition 196
- Computer Networks and Communications 124
- Control and Systems Engineering 65
- Artificial Intelligence 51
Countries citing papers authored by Haojia Li
This map shows the geographic impact of Haojia Li'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 Haojia Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haojia Li more than expected).
Fields of papers citing papers by Haojia Li
This network shows the impact of papers produced by Haojia Li. 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 Haojia Li. The network helps show where Haojia Li may publish in the future.
Co-authorship network of co-authors of Haojia Li
This figure shows the co-authorship network connecting the top 25 collaborators of Haojia Li. A scholar is included among the top collaborators of Haojia Li 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 Haojia Li. Haojia Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 8 | |
| 3 | 5 | |
| 4 | 17 | |
| 5 | 12 | |
| 6 | Swarm of micro flying robots in the wildbreakdown → | 316 |
| 7 | 19 | |
| 8 | 29 |
About Haojia Li
Haojia Li is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Aerospace Engineering, having authored 8 papers that have together received 417 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (6 papers), Robotic Path Planning Algorithms (5 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (196 citations), Aerospace Engineering (217 citations) and Computer Networks and Communications (124 citations). Haojia Li has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Fei Gao, Chao Xu, Yuman Gao, Xin Zhou, Haojian Lu, Qianhao Wang, Tiankai Yang, Xiangyong Wen, Yanjun Cao and Zhepei Wang. Their work appears in journals such as IEEE Transactions on Robotics, IEEE Transactions on Instrumentation and Measurement and Science Robotics.
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.