Weiwei Shan

1.5k citations
117 papers · 902 · h-index 16

Impact in

Papers in

Weiwei Shan

105 papers receiving 874 citations

Peers

Weiwei Shan
Comparison fields: 5 of 84
  • Hardware and Architecture 251
  • Signal Processing 106
  • Artificial Intelligence 285
  • Electrical and Electronic Engineering 506
  • Computer Vision and Pattern Recognition 101
Replace Kwen‐Siong Chong with:
Kwen‐Siong Chong Singapore
Luis Parrilla Spain
Raghavan Kumar United States
Yongtae Kim South Korea
Jintao Zhang China
Marc Renaudin France
Santosh Kumar Vishvakarma India
Marisa López‐Vallejo Spain
Vojtěch Mrázek Czechia
Hongyang Jia China
Weiwei Shan relative to Kwen‐Siong Chong Singapore Kwen‐Siong Chong's profile →
Citations per field
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Kwen‐Siong Chong · 1×
Citations per year

Countries citing papers authored by Weiwei Shan

Since Specialization
Citations

This map shows the geographic impact of Weiwei Shan'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 Weiwei Shan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiwei Shan more than expected).

Fields of papers citing papers by Weiwei Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weiwei Shan. 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 Weiwei Shan. The network helps show where Weiwei Shan may publish in the future.

Co-authors

The 25 scholars most cited alongside Weiwei Shan, 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 Weiwei Shan Line = papers co-authored together Weiwei Shan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202368
2 202062
3 202053
4 202350
5 201536
6 202231
7 202128
8 200826
9 201925
10 201722
11 202021
12 201921
13 201820
14 202318
15 201917
16 201715
17 202213
18 201813
19 201913
20 201712

About Weiwei Shan

Weiwei Shan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Hardware and Architecture, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 117 papers that have together received 902 indexed citations. Recurring topics across this work include Low-power high-performance VLSI design (41 papers), Advancements in Semiconductor Devices and Circuit Design (19 papers), Semiconductor materials and devices (18 papers), Analog and Mixed-Signal Circuit Design (15 papers), Advanced Memory and Neural Computing (14 papers), VLSI and Analog Circuit Testing (13 papers), Cryptographic Implementations and Security (13 papers) and Chaos-based Image/Signal Encryption (10 papers). The work is most often cited by research in Hardware and Architecture (251 citations), Signal Processing (106 citations), Artificial Intelligence (285 citations), Electrical and Electronic Engineering (506 citations) and Computer Vision and Pattern Recognition (101 citations). Weiwei Shan has collaborated with scholars based in China, United States and Bangladesh. Frequent co-authors include Jun Yang, Longxing Shi, Hao Cai, Minhao Yang, Zhipeng Xu, Mingoo Seok, Shuai Zhang, Chengjun Wu, Yongliang Zhou and Xinning Liu. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Circuits & Systems II Express Briefs, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Access and Fertility and Sterility.

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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