Yanqi Chen
Impact in
- Cognitive Neuroscience top 5%
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
Papers in
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- Advanced Memory and Neural Computing 5
- Perovskite Materials and Applications 1
- Ferroelectric and Negative Capacitance Devices 1
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- Neural dynamics and brain function 3
- Co-authors
- Yonghong Tian (4 shared papers)Timothée Masquelier (4 shared papers)Zhaofei Yu (3 shared papers)Wei Fang (3 shared papers)Tiejun Huang (2 shared papers)Wei Fang (1 shared paper)Guoqi Li (1 shared paper)Huihui Zhou (1 shared paper)
In The Last Decade
Yanqi Chen
6 papers receiving 587 citations
Yanqi Chen's Hit Papers
Peers
Comparison fields: 5 of 54
- Cognitive Neuroscience 315
- Electrical and Electronic Engineering 478
- Artificial Intelligence 214
- Cellular and Molecular Neuroscience 68
- Computational Mathematics 1
Countries citing papers authored by Yanqi Chen
This map shows the geographic impact of Yanqi 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 Yanqi Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanqi Chen more than expected).
Fields of papers citing papers by Yanqi Chen
This network shows the impact of papers produced by Yanqi 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 Yanqi Chen. The network helps show where Yanqi Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Yanqi 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
| # | Work | ||
|---|---|---|---|
| 1 | Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks Hit paper breakdown → | 2021 | 375 |
| 2 | SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence Hit paper breakdown → | 2023 | 184 |
| 3 | 2017 | 16 | |
| 4 | 2024 | 11 | |
| 5 | 2018 | 10 | |
| 6 | 2020 | 2 | |
| 7 | 2026 | 0 | |
| 8 | 2023 | 0 |
About Yanqi Chen
Yanqi Chen is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Mechanical Engineering, Cellular and Molecular Neuroscience and Computational Mechanics, having authored 8 papers that have together received 598 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (5 papers), Neural dynamics and brain function (3 papers), Heat Transfer and Optimization (1 paper), Perovskite Materials and Applications (1 paper), 2D Materials and Applications (1 paper), Neuroscience and Neural Engineering (1 paper), Ferroelectric and Negative Capacitance Devices (1 paper) and Fluid Dynamics and Thin Films (1 paper). The work is most often cited by research in Cognitive Neuroscience (315 citations), Electrical and Electronic Engineering (478 citations), Artificial Intelligence (214 citations), Cellular and Molecular Neuroscience (68 citations) and Computational Mathematics (1 citation). Yanqi Chen has collaborated with scholars based in China, France and Singapore. Frequent co-authors include Yonghong Tian, Timothée Masquelier, Zhaofei Yu, Wei Fang, Tiejun Huang, Wei Fang, Guoqi Li, Huihui Zhou, Jianhao Ding and Liwei Huang. Their work appears in journals such as International Journal of Heat and Mass Transfer, Advanced Electronic Materials, Energies, Science Advances and Frontiers in Neuroscience.
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.