Jingchen Li
Impact in
- Pollution top 5%
- Pharmaceutical and Antibiotic Environmental Impacts
- Water Science and Technology top 5%
- Advanced oxidation water treatment
Papers in
-
- Reinforcement Learning in Robotics 16
- Neural Networks and Reservoir Computing 3
-
- Advanced Neural Network Applications 4
- Co-authors
- Lin Zhao (5 shared papers)Haobin Shi (27 shared papers)Peizhe Sun (4 shared papers)Kao‐Shing Hwang (19 shared papers)Ching‐Hua Huang (2 shared papers)Mingbao Feng (1 shared paper)Yongkui Yang (3 shared papers)Ruochun Zhang (3 shared papers)
- Journals
- Information Sciences (3 papers)International Journal of Fuzzy Systems (3 papers)Neural Computing and Applications (3 papers)Engineering Applications of Artificial Intelligence (2 papers)Knowledge-Based Systems (2 papers)
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Jingchen Li
50 papers receiving 860 citations
Peers
Comparison fields: 5 of 131
- Pollution 154
- Water Science and Technology 182
- Renewable Energy, Sustainability and the Environment 154
- Industrial and Manufacturing Engineering 61
- Neurology 48
Countries citing papers authored by Jingchen Li
This map shows the geographic impact of Jingchen 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 Jingchen Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jingchen Li more than expected).
Fields of papers citing papers by Jingchen Li
This network shows the impact of papers produced by Jingchen 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 Jingchen Li. The network helps show where Jingchen Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Jingchen Li, 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 57 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 167 | |
| 2 | 2021 | 86 | |
| 3 | 2016 | 82 | |
| 4 | 2019 | 76 | |
| 5 | 2017 | 52 | |
| 6 | 2021 | 48 | |
| 7 | 2018 | 45 | |
| 8 | 2023 | 44 | |
| 9 | 2020 | 26 | |
| 10 | 2021 | 25 | |
| 11 | 2022 | 22 | |
| 12 | 2021 | 20 | |
| 13 | 2021 | 17 | |
| 14 | 2023 | 14 | |
| 15 | 2021 | 12 | |
| 16 | 2022 | 10 | |
| 17 | 2023 | 9 | |
| 18 | 2024 | 8 | |
| 19 | 2021 | 8 | |
| 20 | 2023 | 8 |
About Jingchen Li
Jingchen Li is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Pollution and Control and Systems Engineering, having authored 57 papers that have together received 873 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (16 papers), Adaptive Dynamic Programming Control (6 papers), Advanced Neural Network Applications (4 papers), Advanced oxidation water treatment (4 papers), IoT and Edge/Fog Computing (3 papers), Electrowetting and Microfluidic Technologies (3 papers), Asphalt Pavement Performance Evaluation (3 papers) and Neural Networks and Reservoir Computing (3 papers). The work is most often cited by research in Pollution (154 citations), Water Science and Technology (182 citations), Renewable Energy, Sustainability and the Environment (154 citations), Industrial and Manufacturing Engineering (61 citations) and Neurology (48 citations). Jingchen Li has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Lin Zhao, Haobin Shi, Peizhe Sun, Kao‐Shing Hwang, Ching‐Hua Huang, Mingbao Feng, Yongkui Yang, Ruochun Zhang, Huijie Hou and Lin Zhao. Their work appears in journals such as Information Sciences, International Journal of Fuzzy Systems, Neural Computing and Applications, Engineering Applications of Artificial Intelligence and Knowledge-Based Systems.
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.