Hao Chen
- Building and Construction top 2%
- Artificial Intelligence top 5%
- Transportation top 2%
- Media Technology top 2%
- Computer Vision and Pattern Recognition top 5%
- Topics
- Traffic Prediction and Management Techniques (21 papers)Remote-Sensing Image Classification (16 papers)Transportation Planning and Optimization (14 papers)
- Journals
- IEEE Transactions on Geoscience and Remote SensingExpert Systems with ApplicationsIEEE Communications Magazine
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Hao Chen
98 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 130
- Building and Construction 383
- Artificial Intelligence 367
- Transportation 270
- Media Technology 239
- Computer Vision and Pattern Recognition 223
Countries citing papers authored by Hao Chen
This map shows the geographic impact of Hao Chen'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 Hao Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Chen more than expected).
Fields of papers citing papers by Hao Chen
This network shows the impact of papers produced by Hao Chen. 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 Hao Chen. The network helps show where Hao Chen may publish in the future.
Co-authorship network of co-authors of Hao Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Hao Chen. A scholar is included among the top collaborators of Hao Chen 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 Hao Chen. Hao Chen 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 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 4 | |
| 7 | 0 | |
| 8 | 42 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 64 | |
| 12 | 11 | |
| 13 | 8 | |
| 14 | PASH at TREC 2020 Deep Learning Track: Dense Matching for Nested Ranking. | 1 |
| 15 | 9 | |
| 16 | A Multiple Models Ensembling Method in TREC Deep Learning. | 1 |
| 17 | A service model based on SWE for space-aeronautics cooperation earth observing operations | 1 |
| 18 | A Generalized Matrix Algorithm for Reliability Evaluation of Distribution Network Orienting the Least Distribution Sections | 1 |
| 19 | Visual Simulation Technique for the Task Planning System of Imaging Satellites | 1 |
| 20 | Modeling and Simulation of Roaming Volume Data Based on Texture Mapping | 0 |
About Hao Chen
Hao Chen is a scholar working on Building and Construction, Transportation and Media Technology, having authored 111 papers that have together received 1.5k indexed citations. Recurring topics across this work include Traffic Prediction and Management Techniques (21 papers), Remote-Sensing Image Classification (16 papers) and Transportation Planning and Optimization (14 papers). The work is most often cited by research in Transportation (270 citations), Building and Construction (383 citations) and Media Technology (239 citations). Hao Chen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Hesham Rakha, Chun Du, Jiangjiang Wu, Eduard Hovy, Fangxiang Feng, Xiaojie Wang, Ruifan Li, Zhanyu Ma, Jun Li and Senzhang Wang. Their work appears in journals such as IEEE Transactions on Geoscience and Remote Sensing, Expert Systems with Applications and IEEE Communications Magazine.
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.