Bonan Yan
Impact in
-
- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
- CCD and CMOS Imaging Sensors
- Hardware and Architecture top 5%
Papers in
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- Advanced Memory and Neural Computing 47
- Ferroelectric and Negative Capacitance Devices 37
- Semiconductor materials and devices 8
- Co-authors
- Yiran ChenHai LiQing WuYuchao YangRu HuangChenchen LiuBing LiMeng‐Fan Chang
- Journals
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (3 papers)Nature Communications (2 papers)Science China Information Sciences (2 papers)Nature Electronics (2 papers)AIAA Journal (2 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Bonan Yan
59 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 57
- Electrical and Electronic Engineering 871
- Hardware and Architecture 98
- Cellular and Molecular Neuroscience 187
- Artificial Intelligence 212
- Cognitive Neuroscience 78
Countries citing papers authored by Bonan Yan
This map shows the geographic impact of Bonan Yan'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 Bonan Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bonan Yan more than expected).
Fields of papers citing papers by Bonan Yan
This network shows the impact of papers produced by Bonan Yan. 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 Bonan Yan. The network helps show where Bonan Yan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bonan Yan, 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 | 2025 | 7 | |
| 2 | 2024 | 18 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 0 | |
| 7 | 2023 | 46 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 13 | |
| 11 | 2022 | 89 | |
| 12 | 2022 | 5 | |
| 13 | 2022 | 1 | |
| 14 | 2020 | 28 | |
| 15 | 2020 | 3 | |
| 16 | 2019 | 72 | |
| 17 | 2018 | 18 | |
| 18 | 2017 | 13 | |
| 19 | 2015 | 13 | |
| 20 | 2010 | 31 |
About Bonan Yan
Bonan Yan is a scholar working on Electrical and Electronic Engineering, Hardware and Architecture, Cellular and Molecular Neuroscience, Artificial Intelligence and Atomic and Molecular Physics, and Optics, having authored 65 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (47 papers), Ferroelectric and Negative Capacitance Devices (37 papers), Magnetic properties of thin films (9 papers), Neuroscience and Neural Engineering (8 papers), Semiconductor materials and devices (8 papers), Neural Networks and Reservoir Computing (6 papers), Photoreceptor and optogenetics research (5 papers) and Quantum and electron transport phenomena (5 papers). The work is most often cited by research in Electrical and Electronic Engineering (871 citations), Hardware and Architecture (98 citations), Cellular and Molecular Neuroscience (187 citations), Artificial Intelligence (212 citations) and Cognitive Neuroscience (78 citations). Bonan Yan has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Yiran Chen, Hai Li, Qing Wu, Yuchao Yang, Ru Huang, Chenchen Liu, Bing Li, Meng‐Fan Chang, Hao Jiang and Zheng Li. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Nature Communications, Science China Information Sciences, Nature Electronics and AIAA 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.