Huihan Li
Impact in
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
Papers in
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- Advanced Memory and Neural Computing 6
- Ferroelectric and Negative Capacitance Devices 5
- Electric Motor Design and Analysis 1
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- 2D Materials and Applications 2
- Graphene research and applications 1
- Co-authors
- Linfeng Sun (8 shared papers)Zhongrui Wang (5 shared papers)Peng Lin (4 shared papers)Wanxiang Feng (3 shared papers)Yugui Yao (3 shared papers)Xumeng Zhang (2 shared papers)Wei Wang (2 shared papers)Zhong Sun (2 shared papers)
In The Last Decade
Huihan Li
9 papers receiving 292 citations
Huihan Li's Hit Papers
Peers
Comparison fields: 5 of 30
- Cellular and Molecular Neuroscience 93
- Electrical and Electronic Engineering 271
- Polymers and Plastics 53
- Cognitive Neuroscience 29
- Materials Chemistry 68
Countries citing papers authored by Huihan Li
This map shows the geographic impact of Huihan 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 Huihan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huihan Li more than expected).
Fields of papers citing papers by Huihan Li
This network shows the impact of papers produced by Huihan 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 Huihan Li. The network helps show where Huihan Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Huihan 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
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 146 | |
| 2 | Relaxor Antiferroelectric Dynamics for Neuromorphic Computing Hit paper breakdown → | 2025 | 43 |
| 3 | 2022 | 37 | |
| 4 | 2021 | 33 | |
| 5 | 2022 | 18 | |
| 6 | 2024 | 17 | |
| 7 | 2025 | 6 | |
| 8 | 2024 | 1 | |
| 9 | 2024 | 1 |
About Huihan Li
Huihan Li is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Cellular and Molecular Neuroscience, Control and Systems Engineering and Artificial Intelligence, having authored 9 papers that have together received 302 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Ferroelectric and Negative Capacitance Devices (5 papers), 2D Materials and Applications (2 papers), Electric Motor Design and Analysis (1 paper), Magnetic Bearings and Levitation Dynamics (1 paper), Neuroscience and Neural Engineering (1 paper), Nanowire Synthesis and Applications (1 paper) and Graphene research and applications (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (93 citations), Electrical and Electronic Engineering (271 citations), Polymers and Plastics (53 citations), Cognitive Neuroscience (29 citations) and Materials Chemistry (68 citations). Huihan Li has collaborated with scholars based in China, Hong Kong and Israel. Frequent co-authors include Linfeng Sun, Zhongrui Wang, Peng Lin, Wanxiang Feng, Yugui Yao, Xumeng Zhang, Wei Wang, Zhong Sun, Rui Yang and Dongliang Yang. Their work appears in journals such as Nature Communications, ACS Nano, IEEE Transactions on Circuits and Systems I Regular Papers, Advanced Materials and Alexandria Engineering Journal.
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.