Dabin Wu
Impact in
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Semiconductor materials and devices
- CCD and CMOS Imaging Sensors
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
Papers in ⓘ
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- Advanced Memory and Neural Computing 4
- Ferroelectric and Negative Capacitance Devices 4
- Semiconductor materials and devices 2
- Low-power high-performance VLSI design 1
- CCD and CMOS Imaging Sensors 1
- Virology 1
- HIV Research and Treatment 1
- Co-authors
- Gert Cauwenberghs (2 shared papers)Siddharth Joshi (2 shared papers)Wenqiang Zhang (2 shared papers)Bin Gao (5 shared papers)Sukru Burc Eryilmaz (2 shared papers)Rajkumar Kubendran (2 shared papers)Weier Wan (2 shared papers)Stephen Deiss (2 shared papers)
- Journals
- Nature (1 paper)IEEE Transactions on Circuits and Systems I Regular Papers (1 paper)Addictive Behaviors (1 paper)
- Partner nations
- ChinaUnited StatesUganda
In The Last Decade
Dabin Wu
6 papers receiving 622 citations
Hit Papers
Peers
Comparison fields: 5 of 53
- Electrical and Electronic Engineering 578
- Cellular and Molecular Neuroscience 163
- Hardware and Architecture 32
- Artificial Intelligence 137
- Cognitive Neuroscience 73
Countries citing papers authored by Dabin Wu
This map shows the geographic impact of Dabin Wu'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 Dabin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dabin Wu more than expected).
Fields of papers citing papers by Dabin Wu
This network shows the impact of papers produced by Dabin Wu. 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 Dabin Wu. The network helps show where Dabin Wu may publish in the future.
Co-authors
The 20 scholars most cited alongside Dabin Wu, 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 | A compute-in-memory chip based on resistive random-access memory Hit paper breakdown → | 2022 | 511 |
| 2 | 2020 | 106 | |
| 3 | 2005 | 11 | |
| 4 | 2023 | 3 | |
| 5 | 2020 | 2 | |
| 6 | 2021 | 2 | |
| 7 | 2012 | 1 |
About Dabin Wu
Dabin Wu is a scholar working on Electrical and Electronic Engineering, Virology, Control and Systems Engineering, Computer Vision and Pattern Recognition and Atomic and Molecular Physics, and Optics, having authored 7 papers that have together received 636 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (4 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Semiconductor materials and devices (2 papers), HIV Research and Treatment (1 paper), Thermal Analysis in Power Transmission (1 paper), HIV, Drug Use, Sexual Risk (1 paper), Low-power high-performance VLSI design (1 paper) and CCD and CMOS Imaging Sensors (1 paper). The work is most often cited by research in Electrical and Electronic Engineering (578 citations), Cellular and Molecular Neuroscience (163 citations), Hardware and Architecture (32 citations), Artificial Intelligence (137 citations) and Cognitive Neuroscience (73 citations). Dabin Wu has collaborated with scholars based in China, United States and Uganda. Frequent co-authors include Gert Cauwenberghs, Siddharth Joshi, Wenqiang Zhang, Bin Gao, Sukru Burc Eryilmaz, Rajkumar Kubendran, Weier Wan, Stephen Deiss, Priyanka Raina and Huaqiang Wu. Their work appears in journals such as Nature, IEEE Transactions on Circuits and Systems I Regular Papers and Addictive Behaviors.
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.