Daniel Belkin
Impact in
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- Neuroscience and Neural Engineering
- Photoreceptor and optogenetics research
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- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- CCD and CMOS Imaging Sensors
- Semiconductor materials and devices
Papers in
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- Neuroscience and Neural Engineering 3
- Photoreceptor and optogenetics research 1
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- Advanced Memory and Neural Computing 5
- Ferroelectric and Negative Capacitance Devices 4
- Semiconductor materials and devices 1
- Co-authors
- Hao Jiang (5 shared papers)Zhongrui Wang (5 shared papers)Can Li (5 shared papers)Qiangfei Xia (5 shared papers)Yunning Li (4 shared papers)Mark D. Barnell (4 shared papers)Qing Wu (4 shared papers)R. Stanley Williams (3 shared papers)
- Journals
- Nature Communications (2 papers)PRX Quantum (1 paper)Nature Electronics (1 paper)Russian Journal of Nondestructive Testing (1 paper)
- Partner nations
- United StatesRussiaChina
In The Last Decade
Daniel Belkin
6 papers receiving 1.5k citations
Daniel Belkin's Hit Papers
Peers
Comparison fields: 5 of 47
- Cellular and Molecular Neuroscience 584
- Electrical and Electronic Engineering 1.4k
- Cognitive Neuroscience 305
- Hardware and Architecture 82
- Polymers and Plastics 124
Countries citing papers authored by Daniel Belkin
This map shows the geographic impact of Daniel Belkin'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 Daniel Belkin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Belkin more than expected).
Fields of papers citing papers by Daniel Belkin
This network shows the impact of papers produced by Daniel Belkin. 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 Daniel Belkin. The network helps show where Daniel Belkin may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Belkin, 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 | Efficient and self-adaptive in-situ learning in multilayer memristor neural networks Hit paper breakdown → | 2018 | 767 |
| 2 | A novel true random number generator based on a stochastic diffusive memristor Hit paper breakdown → | 2017 | 382 |
| 3 | Reinforcement learning with analogue memristor arrays Hit paper breakdown → | 2019 | 323 |
| 4 | 2018 | 43 | |
| 5 | 2019 | 5 | |
| 6 | 2024 | 2 | |
| 7 | 2020 | 0 |
About Daniel Belkin
Daniel Belkin is a scholar working on Cellular and Molecular Neuroscience, Electrical and Electronic Engineering, Computational Theory and Mathematics, Cognitive Neuroscience and Atomic and Molecular Physics, and Optics, having authored 7 papers that have together received 1.5k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Neuroscience and Neural Engineering (3 papers), Semiconductor materials and devices (1 paper), Quantum Computing Algorithms and Architecture (1 paper), Neural dynamics and brain function (1 paper), Complexity and Algorithms in Graphs (1 paper) and Photoreceptor and optogenetics research (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (584 citations), Electrical and Electronic Engineering (1.4k citations), Cognitive Neuroscience (305 citations), Hardware and Architecture (82 citations) and Polymers and Plastics (124 citations). Daniel Belkin has collaborated with scholars based in United States, Russia and China. Frequent co-authors include Hao Jiang, Zhongrui Wang, Can Li, Qiangfei Xia, Yunning Li, Mark D. Barnell, Qing Wu, R. Stanley Williams, John Paul Strachan and Miao Hu. Their work appears in journals such as Nature Communications, PRX Quantum, Nature Electronics and Russian Journal of Nondestructive Testing.
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.