Zhidan Liu
- Transportation top 2%
- Human Mobility and Location-Based Analysis 10
- Building and Construction top 5%
- Traffic Prediction and Management Techniques 4
- Automotive Engineering top 10%
- Transportation and Mobility Innovations 6
- Human-Computer Interaction top 10%
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- Energy Efficient Wireless Sensor Networks 7
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- Indoor and Outdoor Localization Technologies 6
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- Recommender Systems and Techniques 5
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- Human Pose and Action Recognition 4
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- Advanced Graph Neural Networks 3
Zhidan Liu
36 papers receiving 563 citations
Peers
Comparison fields: 5 of 68
- Transportation 173
- Computer Science Applications 100
- Building and Construction 121
- Automotive Engineering 99
- Human-Computer Interaction 33
Countries citing papers authored by Zhidan Liu
This map shows the geographic impact of Zhidan Liu'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 Zhidan Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhidan Liu more than expected).
Fields of papers citing papers by Zhidan Liu
This network shows the impact of papers produced by Zhidan Liu. 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 Zhidan Liu. The network helps show where Zhidan Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Zhidan Liu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 14 | |
| 6 | 2023 | 4 | |
| 7 | 2022 | 3 | |
| 8 | 2022 | 35 | |
| 9 | 2022 | 14 | |
| 10 | 2022 | 5 | |
| 11 | 2021 | 13 | |
| 12 | 2020 | 37 | |
| 13 | 2020 | 71 | |
| 14 | 2019 | 18 | |
| 15 | When Wearable Sensing Meets Arm Tracking. | 2019 | 1 |
| 16 | 2018 | 35 | |
| 17 | 2017 | 51 | |
| 18 | 2016 | 59 | |
| 19 | 2014 | 3 | |
| 20 | 2013 | 1 |
About Zhidan Liu
Zhidan Liu is a scholar working on Transportation, Computer Vision and Pattern Recognition, Automotive Engineering, Computer Science Applications and Building and Construction, having authored 38 papers that have together received 573 indexed citations. Recurring topics across this work include Human Mobility and Location-Based Analysis (10 papers), Energy Efficient Wireless Sensor Networks (7 papers), Indoor and Outdoor Localization Technologies (6 papers), Transportation and Mobility Innovations (6 papers), Recommender Systems and Techniques (5 papers), Human Pose and Action Recognition (4 papers), Traffic Prediction and Management Techniques (4 papers) and Advanced Graph Neural Networks (3 papers). The work is most often cited by research in Transportation (173 citations), Computer Science Applications (100 citations), Building and Construction (121 citations), Automotive Engineering (99 citations) and Human-Computer Interaction (33 citations). Zhidan Liu has collaborated with scholars based in China, Hong Kong and Singapore. Frequent co-authors include Kaishun Wu, Zhenjiang Li, Mo Li, Jiangzhou Li, Wei Xing, Pengfei Zhou, Tianzhang Xing, Dongming Lu, Yang Liu and Shiqi Jiang. Their work appears in journals such as IEEE Transactions on Mobile Computing, IEEE Internet of Things Journal, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Knowledge and Data Engineering and IEEE Transactions on Big Data.
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.