De Ma

922 citations

44 papers · 592 · h-index 14

Impact in

Cognitive Neuroscience top 10%
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
Electrical and Electronic Engineering top 10%
- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors

Papers in

Electrical and Electronic Engineering 28
- Advanced Memory and Neural Computing 24
- Ferroelectric and Negative Capacitance Devices 7
- CCD and CMOS Imaging Sensors 5
Cognitive Neuroscience 14
- Neural dynamics and brain function 14

Co-authors: Gang Pan (18 shared papers)Xiaolei Zhu (7 shared papers)Zonghua Gu (5 shared papers)Huajin Tang (8 shared papers)Qi Xu (3 shared papers)Xiaoqiang Xu (2 shared papers)Ming Zhang (4 shared papers)Qianhui Liu (3 shared papers)
Journals: IEEE Transactions on Cognitive and Developmental Systems (2 papers)Neural Networks (2 papers)IEEE Access (2 papers)Neurocomputing (2 papers)IEEE Transactions on Very Large Scale Integration (VLSI) Systems (1 paper)
Partner nations: China Singapore Sweden

In The Last Decade

De Ma

35 papers receiving 568 citations

Peers

Countries citing papers authored by De Ma

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Darwin: A neuromorphic hardware co-processor based on spiking neural networks Journal of Systems Architecture ·De Ma, Juncheng Shen, Zonghua Gu, Ming Zhang, Xiaolei Zhu, Xiaoqiang Xu, Qi Xu, Yangjing Shen, Gang Pan	2017	112
2	Darwin: a neuromorphic hardware co-processor based on Spiking Neural Networks Science China Information Sciences ·Juncheng Shen, De Ma, Zonghua Gu, Ming Zhang, Xiaolei Zhu, Xiaoqiang Xu, Qi Xu, Yangjing Shen, Gang Pan	2015	67
3	Event-based Action Recognition Using Motion Information and Spiking Neural Networks Qianhui Liu, Dong Xing, Huajin Tang, De Ma, Gang Pan	2021	49
4	Phosphatidylserine-microbubble targeting-activated microglia/macrophage in inflammation combined with ultrasound for breaking through the blood–brain barrier Journal of Neuroinflammation ·Ranran Zhao, Jie Jiang, Huiwen Li, Min Chen, Renfa Liu, Sujuan Sun, De Ma, Xiaolong Liang, Shumin Wang	2018	38
5	Relative ordering learning in spiking neural network for pattern recognition Neurocomputing ·Zhitao Lin, De Ma, Jianyi Meng, Linna Chen	2017	30
6	A Modular Approximation Methodology for Efficient Fixed-Point Hardware Implementation of the Sigmoid Function IEEE Transactions on Industrial Electronics ·Zhe Pan, Zonghua Gu, Xiaohong Jiang, Guoquan Zhu, De Ma	2022	29
7	Effect of post-annealing treatments on the properties of Zn1−xCdxO films on glass substrates Materials Science and Engineering B ·De Ma, Zheyu Ye, Jingyun Huang, Li Zhu, Binghui Zhao, Jun He	2004	29
8	TensorClog: An Imperceptible Poisoning Attack on Deep Neural Network Applications IEEE Access ·Juncheng Shen, Xiaolei Zhu, De Ma	2019	27
9	Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence ·Lang Feng, Qianhui Liu, Huajin Tang, De Ma, Gang Pan	2022	27
10	Darwin3: a large-scale neuromorphic chip with a novel ISA and on-chip learning National Science Review ·De Ma, Xiaofei Jin, Shichun Sun, Yitao Li, Xundong Wu, Youneng Hu, Fangchao Yang, Huajin Tang, Xiaolei Zhu, Peng Lin, Gang Pan	2024	23
11	Scalable NoC-based Neuromorphic Hardware Learning and Inference Haowen Fang, Amar Shrestha, De Ma, Qinru Qiu	2018	22
12	An Efficient Learning Algorithm for Direct Training Deep Spiking Neural Networks IEEE Transactions on Cognitive and Developmental Systems ·Xiaolei Zhu, Baixin Zhao, De Ma, Huajin Tang	2021	18
13	Bio-plausible reconfigurable spiking neuron for neuromorphic computing Science Advances ·Xiao Yu, Y. F. Liu, Bihua Zhang, Peng Chen, Huaze Zhu, Enhui He, Jiayi Zhao, Wenju Huo, Xiaofei Jin, Xumeng Zhang, Hao Jiang, De Ma, Qian Zheng, Huajin Tang, Peng Lin, Wei Kong, Gang Pan	2025	14
14	Efficient Spiking Neural Networks With Logarithmic Temporal Coding IEEE Access ·Ming Zhang, Zonghua Gu, Nenggan Zheng, De Ma, Gang Pan	2020	14
15	Efficient spiking neural network design via neural architecture search Neural Networks ·Jiaqi Yan, Qianhui Liu, Malu Zhang, Lang Feng, De Ma, Haizhou Li, Gang Pan	2024	10
16	Hardware Implementation of Softmax Function Based on Piecewise LUT Xiao Dong, Xiaolei Zhu, De Ma	2019	10
17	Quantisation and pooling method for low‐inference‐latency spiking neural networks Electronics Letters ·Zhitao Lin, Juncheng Shen, De Ma, Jianyi Meng	2017	10
18	R-SNN: Region-Based Spiking Neural Network for Object Detection IEEE Transactions on Cognitive and Developmental Systems ·Xiaobo Jin, Ming Zhang, Rui Yan, Gang Pan, De Ma	2023	8
19	A Q-routing based self-regulated routing scheme for network-on-chip Yande Xiang, Jianyi Meng, De Ma	2017	7
20	Darwin-S: A Reference Software Architecture for Brain-Inspired Computers Computer ·Shuiguang Deng, Pan Lv, Ouwen Jin, Schahram Dustdar, Ying Li, De Ma, Zhaohui Wu, Gang Pan	2022	6

About De Ma

De Ma is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Artificial Intelligence, Cellular and Molecular Neuroscience and Computer Vision and Pattern Recognition, having authored 44 papers that have together received 592 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (24 papers), Neural dynamics and brain function (14 papers), Ferroelectric and Negative Capacitance Devices (7 papers), Neural Networks and Applications (5 papers), Parallel Computing and Optimization Techniques (5 papers), CCD and CMOS Imaging Sensors (5 papers), Embedded Systems Design Techniques (5 papers) and Photoreceptor and optogenetics research (5 papers). The work is most often cited by research in Cognitive Neuroscience (210 citations), Electrical and Electronic Engineering (405 citations), Artificial Intelligence (197 citations), Cellular and Molecular Neuroscience (94 citations) and Hardware and Architecture (17 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 Zhitao Lin. Their work appears in journals such as IEEE Transactions on Cognitive and Developmental Systems, Neural Networks, IEEE Access, Neurocomputing and IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

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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De Ma

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About De Ma

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