De Ma

922 total citations
44 papers, 592 citations indexed

About

De Ma is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, De Ma has authored 44 papers receiving a total of 592 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Electrical and Electronic Engineering, 14 papers in Cognitive Neuroscience and 13 papers in Artificial Intelligence. Recurrent topics in De Ma's work include Advanced Memory and Neural Computing (24 papers), Neural dynamics and brain function (14 papers) and Ferroelectric and Negative Capacitance Devices (7 papers). De Ma is often cited by papers focused on Advanced Memory and Neural Computing (24 papers), Neural dynamics and brain function (14 papers) and Ferroelectric and Negative Capacitance Devices (7 papers). De Ma collaborates with scholars based in China, Singapore and Sweden. De Ma's co-authors include Gang Pan, Xiaolei Zhu, Zonghua Gu, Huajin Tang, Qi Xu, Xiaoqiang Xu, Ming Zhang, Qianhui Liu, Jianyi Meng and Zhitao Lin and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Science Advances and IEEE Access.

In The Last Decade

De Ma

35 papers receiving 568 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
De Ma China	14	405	210	197	94	47	44	592
Morteza Hosseini United States	10	446 1.1×	170 0.8×	223 1.1×	144 1.5×	71 1.5×	19	607
Corey Lammie Australia	12	362 0.9×	142 0.7×	138 0.7×	113 1.2×	46 1.0×	31	511
Olga Krestinskaya Kazakhstan	12	615 1.5×	182 0.9×	192 1.0×	207 2.2×	48 1.0×	41	719
Arnab Neelim Mazumder United States	8	441 1.1×	127 0.6×	207 1.1×	132 1.4×	65 1.4×	19	578
Indranil Chakraborty United States	15	680 1.7×	91 0.4×	202 1.0×	105 1.1×	75 1.6×	36	815
Xiaoxin Cui China	11	473 1.2×	78 0.4×	134 0.7×	87 0.9×	41 0.9×	134	577
Aaron R. Voelker Canada	9	478 1.2×	324 1.5×	252 1.3×	140 1.5×	27 0.6×	18	642
Nitin Rathi United States	12	390 1.0×	167 0.8×	155 0.8×	61 0.6×	28 0.6×	18	553
Stefan Schliebs New Zealand	9	402 1.0×	320 1.5×	333 1.7×	103 1.1×	19 0.4×	14	621
Bill Kay United States	10	643 1.6×	162 0.8×	333 1.7×	166 1.8×	16 0.3×	29	812

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-authorship network of co-authors of De Ma

This figure shows the co-authorship network connecting the top 25 collaborators of De Ma. A scholar is included among the top collaborators of De Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with De Ma. De Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sun, Ruimin, et al.. (2025). Post-training quantization for efficient ANN-SNN conversion. Neural Networks. 191. 107832–107832.

Yu, Xiao, Peng Chen, Huaze Zhu, et al.. (2025). Bio-plausible reconfigurable spiking neuron for neuromorphic computing. Science Advances. 11(6). eadr6733–eadr6733. 14 indexed citations

Gu, Zonghua, et al.. (2025). Training multi-bit Spiking Neural Network with Virtual Neurons. Neurocomputing. 634. 129825–129825.

Xing, Qinghui, Ming Zhang, De Ma, et al.. (2025). Mapping Large-Scale Spiking Neural Network on Arbitrary Meshed Neuromorphic Hardware. IEEE Transactions on Parallel and Distributed Systems. 36(11). 2325–2340.

Wang, Lei, et al.. (2024). LSM-Based Hotspot Prediction and Hotspot-Aware Routing in NoC-Based Neuromorphic Processor. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 32(7). 1239–1252. 4 indexed citations

Xu, Qi, et al.. (2024). RSNN: Recurrent Spiking Neural Networks for Dynamic Spatial-Temporal Information Processing. 10602–10610. 5 indexed citations

Wang, Chao, et al.. (2024). Learning improvement of spiking neural networks with dynamic adaptive hyperparameter neurons. Applied Intelligence. 54(19). 9158–9176. 1 indexed citations

Ma, De, et al.. (2024). Darwin3: a large-scale neuromorphic chip with a novel ISA and on-chip learning. National Science Review. 11(5). nwae102–nwae102. 23 indexed citations

Jin, Xiaobo, Ming Zhang, Rui Yan, Gang Pan, & De Ma. (2023). R-SNN: Region-Based Spiking Neural Network for Object Detection. IEEE Transactions on Cognitive and Developmental Systems. 16(3). 810–817. 8 indexed citations

10.

Gu, Zonghua, et al.. (2022). A Modular Approximation Methodology for Efficient Fixed-Point Hardware Implementation of the Sigmoid Function. IEEE Transactions on Industrial Electronics. 69(10). 10694–10703. 29 indexed citations

11.

Deng, Shuiguang, Schahram Dustdar, Ying Li, et al.. (2022). Darwin-S: A Reference Software Architecture for Brain-Inspired Computers. Computer. 55(5). 51–63. 6 indexed citations

12.

Zhu, Xiaolei, et al.. (2021). An Efficient Learning Algorithm for Direct Training Deep Spiking Neural Networks. IEEE Transactions on Cognitive and Developmental Systems. 14(3). 847–856. 18 indexed citations

13.

Zhang, Ming, Zonghua Gu, Nenggan Zheng, De Ma, & Gang Pan. (2020). Efficient Spiking Neural Networks With Logarithmic Temporal Coding. IEEE Access. 8. 98156–98167. 14 indexed citations

14.

Zhu, Xiaolei, et al.. (2019). TensorClog: An Imperceptible Poisoning Attack on Deep Neural Network Applications. IEEE Access. 7. 41498–41506. 27 indexed citations

15.

Zhao, Ranran, Jie Jiang, Huiwen Li, et al.. (2018). Phosphatidylserine-microbubble targeting-activated microglia/macrophage in inflammation combined with ultrasound for breaking through the blood–brain barrier. Journal of Neuroinflammation. 15(1). 334–334. 38 indexed citations

16.

Lin, Zhitao, et al.. (2017). Relative ordering learning in spiking neural network for pattern recognition. Neurocomputing. 275. 94–106. 30 indexed citations

17.

Meng, Jianyi, et al.. (2017). A Q-routing based self-regulated routing scheme for network-on-chip. 177–181. 7 indexed citations

18.

Huang, Kai, Xiaoxu Zhang, Min Yu, et al.. (2015). Profiling and annotation combined method for multimedia application specific MPSoC performance estimation. Frontiers of Information Technology & Electronic Engineering. 16(2). 135–151. 5 indexed citations

19.

Ma, De. (2010). Research and Application on Grey Forecasting the GM(1,1) Model. 2 indexed citations

20.

Ma, De, et al.. (2004). Effect of post-annealing treatments on the properties of Zn1−xCdxO films on glass substrates. Materials Science and Engineering B. 111(1). 9–13. 29 indexed citations

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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