Bonan Yan

1.4k citations
65 papers · 1.0k indexed · h-index 19

Impact in

Papers in

Bonan Yan

59 papers receiving 1.0k citations

Peers

Bonan Yan
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
Replace Cheng-Xin Xue with:
Cheng-Xin Xue Taiwan
Indranil Chakraborty United States
Guy Satat United States
Hongwu Jiang United States
Greg Snider United States
Yen-Cheng Chiu Taiwan
Lukas Kull Switzerland
B.A. Minch United States
Joachim Becker Germany
Phil Knag United States
Bonan Yan relative to Cheng-Xin Xue Taiwan Cheng-Xin Xue's profile →
Citations per field
00.5×6.7×
Cheng-Xin Xue · 1×
Citations per year

Countries citing papers authored by Bonan Yan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Bonan Yan Line = papers co-authored together Bonan Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20257
2 202418
3 20242
4 20242
5 20243
6 20240
7 202346
8 20234
9 20230
10 202313
11 202289
12 20225
13 20221
14 202028
15 20203
16 201972
17 201818
18 201713
19 201513
20 201031

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.

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