Guillaume Prenat

2.1k total citations
53 papers, 732 citations indexed

About

Guillaume Prenat is a scholar working on Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics and Artificial Intelligence. According to data from OpenAlex, Guillaume Prenat has authored 53 papers receiving a total of 732 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Electrical and Electronic Engineering, 31 papers in Atomic and Molecular Physics, and Optics and 9 papers in Artificial Intelligence. Recurrent topics in Guillaume Prenat's work include Magnetic properties of thin films (31 papers), Advanced Memory and Neural Computing (24 papers) and Ferroelectric and Negative Capacitance Devices (13 papers). Guillaume Prenat is often cited by papers focused on Magnetic properties of thin films (31 papers), Advanced Memory and Neural Computing (24 papers) and Ferroelectric and Negative Capacitance Devices (13 papers). Guillaume Prenat collaborates with scholars based in France, Germany and China. Guillaume Prenat's co-authors include B. Diény, Grégory Di Pendina, Weisheng Zhao, Kotb Jabeur, Weisheng Zhao, Jacques‐Olivier Klein, Virgile Javerliac, R. C. Sousa, Erya Deng and L. D. Buda-Prejbeanu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

Guillaume Prenat

49 papers receiving 709 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guillaume Prenat France 15 569 425 101 78 76 53 732
Ryusuke Nebashi Japan 12 644 1.1× 341 0.8× 67 0.7× 112 1.4× 64 0.8× 50 762
Jonathan Harms United States 12 469 0.8× 445 1.0× 113 1.1× 52 0.7× 85 1.1× 15 641
Kazutaka Ikegami Japan 13 495 0.9× 336 0.8× 75 0.7× 111 1.4× 43 0.6× 32 623
Sri Harsha Choday United States 15 743 1.3× 484 1.1× 52 0.5× 60 0.8× 104 1.4× 23 872
Noboru Sakimura Japan 17 824 1.4× 380 0.9× 64 0.6× 118 1.5× 55 0.7× 40 934
Eric Belhaire France 12 557 1.0× 354 0.8× 48 0.5× 89 1.1× 32 0.4× 44 675
Masanori Natsui Japan 18 837 1.5× 373 0.9× 44 0.4× 176 2.3× 53 0.7× 90 952
Ki Chul Chun United States 11 526 0.9× 209 0.5× 61 0.6× 121 1.6× 61 0.8× 18 640
Georgios Panagopoulos United States 14 633 1.1× 282 0.7× 45 0.4× 64 0.8× 24 0.3× 32 694
Rajendra Bishnoi Germany 18 909 1.6× 436 1.0× 95 0.9× 259 3.3× 57 0.8× 62 1.1k

Countries citing papers authored by Guillaume Prenat

Since Specialization
Citations

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

Fields of papers citing papers by Guillaume Prenat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guillaume Prenat

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

All Works

20 of 20 papers shown
1.
Incorvia, Jean Anne C., T. Patrick Xiao, Azad Naeemi, et al.. (2024). Spintronics for achieving system-level energy-efficient logic. 1(11). 700–713. 4 indexed citations
2.
Prenat, Guillaume, et al.. (2024). Spatial-SpinDrop: Spatial Dropout-Based Binary Bayesian Neural Network With Spintronics Implementation. IEEE Transactions on Nanotechnology. 23. 636–643.
3.
Prenat, Guillaume, et al.. (2024). Trade-Offs in Neural Network Compression: Quantized and Binary Models for Keyword Spotting. SPIRE - Sciences Po Institutional REpository. 1–4.
4.
Beilliard, Yann, F. Arnaud, Kévin Garello, et al.. (2023). A tunable and versatile 28 nm FD-SOI crossbar output circuit for low power analog SNN inference with eNVM synapses. Solid-State Electronics. 209. 108779–108779. 2 indexed citations
5.
Delaët, B., B. Viala, Guillaume Prenat, et al.. (2023). Designing networks of resistively-coupled stochastic Magnetic Tunnel Junctions for energy-based optimum search. HAL (Le Centre pour la Communication Scientifique Directe). 1–4. 4 indexed citations
6.
Prenat, Guillaume, et al.. (2023). SpinDrop: Dropout-Based Bayesian Binary Neural Networks With Spintronic Implementation. IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 13(1). 150–164. 12 indexed citations
7.
Prenat, Guillaume, et al.. (2022). A Fast, Energy Efficient and Tunable Magnetic Tunnel Junction Based Bitstream Generator for Stochastic Computing. IEEE Transactions on Circuits and Systems I Regular Papers. 69(8). 3251–3259. 6 indexed citations
8.
Pendina, Grégory Di, et al.. (2020). Spin-Transfer Torque Magnetic Tunnel Junction for Single-Event Effects Mitigation in IC Design. IEEE Transactions on Nuclear Science. 67(7). 1674–1681. 2 indexed citations
9.
Vila, L., U. Ebels, R. C. Sousa, et al.. (2020). A multifunctional standardized magnetic tunnel junction stack embedding sensor, memory and oscillator functionality. Journal of Magnetism and Magnetic Materials. 505. 166647–166647. 11 indexed citations
10.
Jabeur, Kotb, Grégory Di Pendina, Guillaume Prenat, L. D. Buda-Prejbeanu, & B. Diény. (2014). Compact Modeling of a Magnetic Tunnel Junction Based on Spin Orbit Torque. IEEE Transactions on Magnetics. 50(7). 1–8. 32 indexed citations
11.
Wei, Guo, Guillaume Prenat, & B. Diény. (2014). A novel architecture of non-volatile magnetic arithmetic logic unit using magnetic tunnel junctions. Journal of Physics D Applied Physics. 47(16). 165001–165001. 14 indexed citations
12.
Pendina, Grégory Di, Kotb Jabeur, & Guillaume Prenat. (2014). Hybrid CMOS/magnetic Process Design Kit and SOT-based non-volatile standard cell architectures. 8. 692–699. 2 indexed citations
13.
Prenat, Guillaume, et al.. (2013). Nonvolatile runtime-reconfigurable FPGA secured through MRAM-based periodic refresh. 170–173. 1 indexed citations
14.
Azevedo, João, A. Virazel, Alberto Bosio, et al.. (2012). Impact of resistive-open defects on the heat current of TAS-MRAM architectures. Design, Automation, and Test in Europe. 532–537. 3 indexed citations
15.
Azevedo, João, A. Virazel, Alberto Bosio, et al.. (2012). Coupling-based resistive-open defects in TAS-MRAM architectures. HAL (Le Centre pour la Communication Scientifique Directe). 1–1. 2 indexed citations
16.
Prenat, Guillaume, et al.. (2011). Hybrid CMOS/magnetic process design kit and application to the design of high-performances non-volatile logic circuits. International Conference on Computer Aided Design. 240–245. 3 indexed citations
17.
Javerliac, Virgile, et al.. (2008). Towards an ultra-low power, high density and non-volatile Ternary CAM. 1–7. 6 indexed citations
18.
Prenat, Guillaume, et al.. (2007). CMOS/Magnetic Hybrid Architectures. SPIRE - Sciences Po Institutional REpository. 190–193. 37 indexed citations
19.
Prenat, Guillaume, et al.. (2005). A low-cost digital frequency testing approach for mixed-signal devices using ΣΔ modulation. Microelectronics Journal. 36(12). 1080–1090. 16 indexed citations
20.
Mir, Salvador, et al.. (2004). A 0.18 /spl mu/m CMOS implementation of on-chip analogue test signal generation from digital test patterns. Design, Automation, and Test in Europe. 1. 10706. 5 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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