Loai Danial

427 total citations
17 papers, 317 citations indexed

About

Loai Danial is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Loai Danial has authored 17 papers receiving a total of 317 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Electrical and Electronic Engineering, 7 papers in Cognitive Neuroscience and 6 papers in Cellular and Molecular Neuroscience. Recurrent topics in Loai Danial's work include Advanced Memory and Neural Computing (17 papers), CCD and CMOS Imaging Sensors (10 papers) and Neural dynamics and brain function (7 papers). Loai Danial is often cited by papers focused on Advanced Memory and Neural Computing (17 papers), CCD and CMOS Imaging Sensors (10 papers) and Neural dynamics and brain function (7 papers). Loai Danial collaborates with scholars based in Israel, United States and Austria. Loai Danial's co-authors include Shahar Kvatinsky, Nicolás Wainstein, Ramez Daniel, Evgeny Pikhay, Yakov Roizin, V.K. Gupta, Nimrod Wald, Ron Weiss, Wei Wang and Yang Li and has published in prestigious journals such as Nature Communications, Applied Physics Letters and IEEE Transactions on Signal Processing.

In The Last Decade

Loai Danial

17 papers receiving 316 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Loai Danial Israel 8 267 97 84 35 30 17 317
Roland Mathis Switzerland 5 312 1.2× 82 0.8× 95 1.1× 19 0.5× 40 1.3× 7 389
Yasmin Halawani United Arab Emirates 9 268 1.0× 79 0.8× 62 0.7× 25 0.7× 8 0.3× 29 318
Jae Hyun In South Korea 9 288 1.1× 122 1.3× 60 0.7× 37 1.1× 8 0.3× 15 359
Ryan Weiss United States 9 324 1.2× 164 1.7× 84 1.0× 58 1.7× 49 1.6× 18 408
Heba Abunahla United Arab Emirates 13 416 1.6× 130 1.3× 32 0.4× 82 2.3× 19 0.6× 35 481
Jeeson Kim South Korea 10 438 1.6× 166 1.7× 48 0.6× 69 2.0× 10 0.3× 21 520
Akshay Wali United States 9 216 0.8× 77 0.8× 35 0.4× 36 1.0× 7 0.2× 14 284
Evgeny Pikhay Israel 10 380 1.4× 79 0.8× 50 0.6× 77 2.2× 30 1.0× 42 439
Mengliu Zhao China 11 159 0.6× 70 0.7× 23 0.3× 47 1.3× 13 0.4× 15 285
Xiaolong Zou China 7 294 1.1× 167 1.7× 87 1.0× 22 0.6× 10 0.3× 12 384

Countries citing papers authored by Loai Danial

Since Specialization
Citations

This map shows the geographic impact of Loai Danial'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 Loai Danial with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Loai Danial more than expected).

Fields of papers citing papers by Loai Danial

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Loai Danial. 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 Loai Danial. The network helps show where Loai Danial may publish in the future.

Co-authorship network of co-authors of Loai Danial

This figure shows the co-authorship network connecting the top 25 collaborators of Loai Danial. A scholar is included among the top collaborators of Loai Danial 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 Loai Danial. Loai Danial is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
1.
Danial, Loai, et al.. (2025). Learning Task-Based Trainable Neuromorphic ADCs via Power-Aware Distillation. IEEE Transactions on Signal Processing. 73. 1246–1261. 2 indexed citations
2.
Danial, Loai, et al.. (2024). Power-Aware Task-Based Learning of Neuromorphic ADCs. 5850–5854. 3 indexed citations
3.
Danial, Loai, et al.. (2022). Synthetic neuromorphic computing in living cells. Nature Communications. 13(1). 5602–5602. 35 indexed citations
4.
Wang, Wei, Loai Danial, Yang Li, et al.. (2022). A memristive deep belief neural network based on silicon synapses. Nature Electronics. 5(12). 870–880. 46 indexed citations
5.
Wang, Wei, et al.. (2021). Physical based compact model of Y-Flash memristor for neuromorphic computation. Applied Physics Letters. 119(26). 10 indexed citations
6.
Danial, Loai, et al.. (2020). Cytomorphic Electronics With Memristors for Modeling Fundamental Genetic Circuits. IEEE Transactions on Biomedical Circuits and Systems. 14(3). 386–401. 7 indexed citations
7.
Danial, Loai, V.K. Gupta, Evgeny Pikhay, Yakov Roizin, & Shahar Kvatinsky. (2020). Modeling a Floating-Gate Memristive Device for Computer Aided Design of Neuromorphic Computing. 472–477. 6 indexed citations
8.
Danial, Loai, et al.. (2020). A Pipelined Memristive Neural Network Analog-to-Digital Converter. 1–5. 7 indexed citations
9.
Danial, Loai & Shahar Kvatinsky. (2020). Breaking the Conversion Wall in Mixed-Signal Systems Using Neuromorphic Data Converters. 1–4. 1 indexed citations
10.
11.
Danial, Loai, Evgeny Pikhay, Nicolás Wainstein, et al.. (2019). Two-terminal floating-gate transistors with a low-power memristive operation mode for analogue neuromorphic computing. Nature Electronics. 2(12). 596–605. 122 indexed citations
12.
Danial, Loai, et al.. (2019). Logarithmic Neural Network Data Converters using Memristors for Biomedical Applications. 1–4. 7 indexed citations
13.
Danial, Loai, et al.. (2018). Memristors as Artificial Biochemical Reactions in Cytomorphic Systems. 453. 1–5. 2 indexed citations
14.
Danial, Loai, et al.. (2018). Breaking Through the Speed-Power-Accuracy Tradeoff in ADCs Using a Memristive Neuromorphic Architecture. IEEE Transactions on Emerging Topics in Computational Intelligence. 2(5). 396–409. 40 indexed citations
15.
Danial, Loai & Shahar Kvatinsky. (2018). Real-Time Trainable Data Converters for General Purpose Applications. 34–36. 4 indexed citations
16.
Danial, Loai, et al.. (2017). Modeling biochemical reactions and gene networks with memristors. 453. 1–4. 3 indexed citations
17.
Danial, Loai, et al.. (2017). DIDACTIC: A Data-Intelligent Digital-to-Analog Converter with a Trainable Integrated Circuit using Memristors. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 8(1). 146–158. 15 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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