Hechang Chen
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Topic Modeling
- Metaheuristic Optimization Algorithms Research
- Anomaly Detection Techniques and Applications
- Modeling and Simulation top 10%
Papers in
-
- Reinforcement Learning in Robotics 9
- Topic Modeling 8
- Advanced Graph Neural Networks 8
- AI in cancer detection 5
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- Digital Imaging for Blood Diseases 5
- Co-authors
- Yi Chang (18 shared papers)Bo Yang (15 shared papers)Jiming Liu (4 shared papers)Haiyin Piao (8 shared papers)Hongbin Pei (3 shared papers)Jing Ma (4 shared papers)Zhiwei Yang (5 shared papers)Guanglei Meng (2 shared papers)
- Journals
- IEEE Access (7 papers)Knowledge-Based Systems (7 papers)IEEE Transactions on Neural Networks and Learning Systems (6 papers)Expert Systems with Applications (6 papers)IEEE Transactions on Knowledge and Data Engineering (4 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Hechang Chen
51 papers receiving 689 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 346
- Modeling and Simulation 34
- Computer Vision and Pattern Recognition 145
- Transportation 40
- Aerospace Engineering 123
Countries citing papers authored by Hechang Chen
This map shows the geographic impact of Hechang 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 Hechang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hechang Chen more than expected).
Fields of papers citing papers by Hechang Chen
This network shows the impact of papers produced by Hechang 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 Hechang Chen. The network helps show where Hechang Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Hechang Chen, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 97 | |
| 2 | 2018 | 48 | |
| 3 | 2020 | 44 | |
| 4 | 2021 | 39 | |
| 5 | 2022 | 38 | |
| 6 | 2022 | 34 | |
| 7 | 2020 | 33 | |
| 8 | 2022 | 25 | |
| 9 | 2021 | 23 | |
| 10 | 2023 | 22 | |
| 11 | 2020 | 17 | |
| 12 | 2023 | 16 | |
| 13 | 2021 | 15 | |
| 14 | 2019 | 15 | |
| 15 | 2023 | 13 | |
| 16 | 2023 | 13 | |
| 17 | 2024 | 13 | |
| 18 | 2022 | 13 | |
| 19 | 2016 | 11 | |
| 20 | 2020 | 11 |
About Hechang Chen
Hechang Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Epidemiology, having authored 61 papers that have together received 700 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (9 papers), Topic Modeling (8 papers), Advanced Graph Neural Networks (8 papers), Complex Network Analysis Techniques (8 papers), COVID-19 epidemiological studies (7 papers), Data-Driven Disease Surveillance (6 papers), Digital Imaging for Blood Diseases (5 papers) and AI in cancer detection (5 papers). The work is most often cited by research in Artificial Intelligence (346 citations), Modeling and Simulation (34 citations), Computer Vision and Pattern Recognition (145 citations), Transportation (40 citations) and Aerospace Engineering (123 citations). Hechang Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yi Chang, Bo Yang, Jiming Liu, Haiyin Piao, Hongbin Pei, Jing Ma, Zhiwei Yang, Guanglei Meng, Jiawei Zhang and Deyun Zhou. Their work appears in journals such as IEEE Access, Knowledge-Based Systems, IEEE Transactions on Neural Networks and Learning Systems, Expert Systems with Applications 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.