De Ma
Impact in
- Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
Papers in
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- Neural dynamics and brain function 14
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- Advanced Memory and Neural Computing 26
- Ferroelectric and Negative Capacitance Devices 8
- CCD and CMOS Imaging Sensors 5
- Co-authors
- Gang Pan (19 shared papers)Xiaolei Zhu (8 shared papers)Zonghua Gu (5 shared papers)Huajin Tang (9 shared papers)Qi Xu (3 shared papers)Xiaoqiang Xu (2 shared papers)Ming Zhang (4 shared papers)Qianhui Liu (2 shared papers)
In The Last Decade
De Ma
42 papers receiving 696 citations
Peers
Comparison fields: 5 of 85
- Cognitive Neuroscience 241
- Electrical and Electronic Engineering 481
- Artificial Intelligence 217
- Cellular and Molecular Neuroscience 109
- Hardware and Architecture 23
Countries citing papers authored by De Ma
This map shows the geographic impact of De Ma'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 De Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites De Ma more than expected).
Fields of papers citing papers by De Ma
This network shows the impact of papers produced by De Ma. 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 De Ma. The network helps show where De Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside De Ma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 135 | |
| 2 | 2015 | 72 | |
| 3 | 2021 | 61 | |
| 4 | 2018 | 40 | |
| 5 | 2022 | 38 | |
| 6 | 2022 | 36 | |
| 7 | 2024 | 35 | |
| 8 | 2017 | 32 | |
| 9 | 2025 | 30 | |
| 10 | 2004 | 29 | |
| 11 | 2019 | 27 | |
| 12 | 2018 | 24 | |
| 13 | 2021 | 19 | |
| 14 | 2020 | 17 | |
| 15 | 2019 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 2017 | 11 | |
| 18 | 2017 | 9 | |
| 19 | 2024 | 9 | |
| 20 | 2024 | 7 |
About De Ma
De Ma is a scholar working on Cognitive Neuroscience, Electrical and Electronic Engineering, Hardware and Architecture, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 48 papers that have together received 712 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (26 papers), Neural dynamics and brain function (14 papers), Ferroelectric and Negative Capacitance Devices (8 papers), Neural Networks and Applications (6 papers), Parallel Computing and Optimization Techniques (6 papers), CCD and CMOS Imaging Sensors (5 papers), Embedded Systems Design Techniques (5 papers) and Interconnection Networks and Systems (5 papers). The work is most often cited by research in Cognitive Neuroscience (241 citations), Electrical and Electronic Engineering (481 citations), Artificial Intelligence (217 citations), Cellular and Molecular Neuroscience (109 citations) and Hardware and Architecture (23 citations). De Ma has collaborated with scholars based in China, Singapore and Sweden. Frequent co-authors include Gang Pan, Xiaolei Zhu, Zonghua Gu, Huajin Tang, Qi Xu, Xiaoqiang Xu, Ming Zhang, Qianhui Liu, Jianyi Meng and Dong Xing. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Neurocomputing, IEEE Access, IEEE Transactions on Cognitive and Developmental Systems and Journal of Systems Architecture.
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.