Weier Wan
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- Advanced Memory and Neural Computing 15
- Ferroelectric and Negative Capacitance Devices 11
- CCD and CMOS Imaging Sensors 3
- Semiconductor materials and devices 3
- Hardware and Architecture top 10%
- Artificial Intelligence top 5%
- Machine Learning and ELM 2
- Neural Networks and Reservoir Computing 2
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function 1
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- Interconnection Networks and Systems 1
- Co-authors
- H.‐S. Philip WongHuaqiang WuBin GaoGert CauwenberghsSiddharth JoshiPriyanka RainaSukru Burc EryilmazRajkumar Kubendran
- Cited by
- Electrical and Electronic EngineeringCellular and Molecular NeuroscienceHardware and Architecture
- Journals
- Scientific Reports (2 papers)Nature (1 paper)IEEE Transactions on Electron Devices (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Weier Wan
15 papers receiving 927 citations
Hit Papers
Peers
Comparison fields: 5 of 52
- Electrical and Electronic Engineering 877
- Cellular and Molecular Neuroscience 229
- Hardware and Architecture 51
- Artificial Intelligence 204
- Cognitive Neuroscience 110
Countries citing papers authored by Weier Wan
This map shows the geographic impact of Weier Wan'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 Weier Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weier Wan more than expected).
Fields of papers citing papers by Weier Wan
This network shows the impact of papers produced by Weier Wan. 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 Weier Wan. The network helps show where Weier Wan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Weier Wan, 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 | 0 | |
| 2 | 2024 | 5 | |
| 3 | A compute-in-memory chip based on resistive random-access memorybreakdown → | 2022 | 511 |
| 4 | 2021 | 47 | |
| 5 | One-Shot Learning with Memory-Augmented Neural Networks Using a 64-kbit, 118 GOPS/W RRAM-Based Non-Volatile Associative Memory | 2021 | 7 |
| 6 | 2020 | 106 | |
| 7 | 2020 | 1 | |
| 8 | 2020 | 6 | |
| 9 | 2020 | 30 | |
| 10 | 2020 | 2 | |
| 11 | 2019 | 39 | |
| 12 | 2018 | 119 | |
| 13 | 2018 | 8 | |
| 14 | 2018 | 17 | |
| 15 | 2018 | 19 | |
| 16 | 2016 | 30 |
About Weier Wan
Weier Wan is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence, Hardware and Architecture, Polymers and Plastics and Computational Theory and Mathematics, having authored 16 papers that have together received 947 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (15 papers), Ferroelectric and Negative Capacitance Devices (11 papers), CCD and CMOS Imaging Sensors (3 papers), Semiconductor materials and devices (3 papers), Machine Learning and ELM (2 papers), Neural Networks and Reservoir Computing (2 papers), Neural dynamics and brain function (1 paper) and Interconnection Networks and Systems (1 paper). The work is most often cited by research in Electrical and Electronic Engineering (877 citations), Cellular and Molecular Neuroscience (229 citations), Hardware and Architecture (51 citations), Artificial Intelligence (204 citations) and Cognitive Neuroscience (110 citations). Weier Wan has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include H.‐S. Philip Wong, Huaqiang Wu, Bin Gao, Gert Cauwenberghs, Siddharth Joshi, Priyanka Raina, Sukru Burc Eryilmaz, Rajkumar Kubendran, Stephen Deiss and Wenqiang Zhang. Their work appears in journals such as Scientific Reports, Nature, IEEE Transactions on Electron Devices, Journal of Physics D Applied Physics and IEEE Journal of Solid-State Circuits.
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.