Eduardo Pérez

1.7k total citations
98 papers, 1.3k citations indexed

About

Eduardo Pérez is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Eduardo Pérez has authored 98 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Electrical and Electronic Engineering, 24 papers in Cellular and Molecular Neuroscience and 8 papers in Cognitive Neuroscience. Recurrent topics in Eduardo Pérez's work include Advanced Memory and Neural Computing (87 papers), Ferroelectric and Negative Capacitance Devices (72 papers) and Semiconductor materials and devices (39 papers). Eduardo Pérez is often cited by papers focused on Advanced Memory and Neural Computing (87 papers), Ferroelectric and Negative Capacitance Devices (72 papers) and Semiconductor materials and devices (39 papers). Eduardo Pérez collaborates with scholars based in Germany, Italy and Spain. Eduardo Pérez's co-authors include Christian Wenger, Mamathamba Kalishettyhalli Mahadevaiah, Cristian Zambelli, P. Olivo, Daniele Ielmini, Valerio Milo, Óscar G. Ossorio, J.B. Roldán, F. Jiménez-Molinos and Alessandro Grossi and has published in prestigious journals such as Scientific Reports, The Journal of Physical Chemistry C and Nanoscale.

In The Last Decade

Eduardo Pérez

90 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eduardo Pérez Germany 21 1.2k 410 129 124 118 98 1.3k
Spyros Stathopoulos United Kingdom 14 863 0.7× 392 1.0× 120 0.9× 81 0.7× 107 0.9× 59 946
Dana Wheeler United States 4 730 0.6× 372 0.9× 90 0.7× 79 0.6× 76 0.6× 9 751
Bhaswar Chakrabarti United States 15 979 0.8× 348 0.8× 108 0.8× 122 1.0× 203 1.7× 41 1.1k
YeonJoo Jeong South Korea 21 1.2k 1.0× 539 1.3× 159 1.2× 188 1.5× 173 1.5× 58 1.4k
Changhyuck Sung South Korea 14 854 0.7× 340 0.8× 162 1.3× 96 0.8× 151 1.3× 21 871
Yuhao Sun China 7 633 0.5× 292 0.7× 138 1.1× 167 1.3× 115 1.0× 12 775
Radu Berdan United Kingdom 13 900 0.8× 419 1.0× 106 0.8× 103 0.8× 123 1.0× 23 932
Zizhen Jiang United States 16 979 0.8× 288 0.7× 161 1.2× 53 0.4× 182 1.5× 38 1.0k
Liying Xu China 12 842 0.7× 268 0.7× 132 1.0× 298 2.4× 164 1.4× 24 917
Zhaokun Jing China 7 603 0.5× 275 0.7× 117 0.9× 115 0.9× 48 0.4× 13 639

Countries citing papers authored by Eduardo Pérez

Since Specialization
Citations

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

Fields of papers citing papers by Eduardo Pérez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eduardo Pérez

This figure shows the co-authorship network connecting the top 25 collaborators of Eduardo Pérez. A scholar is included among the top collaborators of Eduardo Pérez 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 Eduardo Pérez. Eduardo Pérez 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.
Pérez, Eduardo, et al.. (2025). Enhancing RRAM Reliability: Exploring the Effects of Al Doping on HfO 2 -Based Devices. IEEE Transactions on Device and Materials Reliability. 25(3). 379–387.
2.
Pérez, Eduardo, et al.. (2025). A Compact One-Transistor-Multiple-RRAM Characterization Platform. IEEE Transactions on Circuits and Systems I Regular Papers. 72(10). 5559–5570.
3.
Vargas, Fabian, et al.. (2025). RRAMulator: An efficient FPGA-based emulator for RRAM crossbar with device variability and energy consumption evaluation. Microelectronics Reliability. 168. 115630–115630.
4.
Maldonado, D., Christian Acal, H. D. Ortiz, et al.. (2025). A comprehensive statistical study of the post-programming conductance drift in HfO2-based memristive devices. Materials Science in Semiconductor Processing. 196. 109668–109668.
7.
Maldonado, D., et al.. (2024). Kinetic Monte Carlo simulation analysis of the conductance drift in Multilevel HfO2-based RRAM devices. Nanoscale. 16(40). 19021–19033. 3 indexed citations
8.
Castán, Helena, et al.. (2024). Forming and Resistive Switching of HfO₂-Based RRAM Devices at Cryogenic Temperature. IEEE Electron Device Letters. 45(12). 2391–2394. 2 indexed citations
9.
García, H., Eduardo Pérez, Christian Wenger, et al.. (2024). On the Asymmetry of Resistive Switching Transitions. Electronics. 13(13). 2639–2639. 1 indexed citations
10.
Maldonado, D., Eduardo Pérez, Rocío Romero‐Zaliz, et al.. (2023). TiN/Ti/HfO2/TiN memristive devices for neuromorphic computing: from synaptic plasticity to stochastic resonance. Frontiers in Neuroscience. 17. 1271956–1271956. 7 indexed citations
11.
Mahadevaiah, Mamathamba Kalishettyhalli, et al.. (2023). Experimental Assessment of Multilevel RRAM-Based Vector-Matrix Multiplication Operations for In-Memory Computing. IEEE Transactions on Electron Devices. 70(4). 2009–2014. 13 indexed citations
12.
Pérez, Eduardo, et al.. (2023). Efficient circuit simulation of a memristive crossbar array with synaptic weight variability. Solid-State Electronics. 209. 108760–108760. 2 indexed citations
13.
Ossorio, Óscar G., H. García, S. Dueñas, et al.. (2021). Performance Assessment of Amorphous HfO 2 -Based RRAM Devices for Neuromorphic Applications. ECS Journal of Solid State Science and Technology. 10(8). 83002–83002. 5 indexed citations
14.
Ossorio, Óscar G., H. García, S. Dueñas, et al.. (2021). Performance Assessment of Amorphous HfO2-Based RRAM Devices for Neuromorphic Applications. ECS Transactions. 102(2). 29–35. 2 indexed citations
15.
Aldana, Samuel, Eduardo Pérez, F. Jiménez-Molinos, Christian Wenger, & J.B. Roldán. (2020). Kinetic Monte Carlo analysis of data retention in Al:HfO 2 -based resistive random access memories. Semiconductor Science and Technology. 35(11). 115012–115012. 25 indexed citations
16.
Pérez, Eduardo, et al.. (2020). Analogue pattern recognition with stochastic switching binary CMOS-integrated memristive devices. Scientific Reports. 10(1). 14450–14450. 30 indexed citations
17.
Mahadevaiah, Mamathamba Kalishettyhalli, et al.. (2020). Neuromorphic on-chip recognition of saliva samples of COPD and healthy controls using memristive devices. Scientific Reports. 10(1). 19742–19742. 16 indexed citations
18.
Niu, Gang, Peng Huang, S. U. Sharath, et al.. (2019). Operando diagnostic detection of interfacial oxygen ‘breathing’ of resistive random access memory by bulk-sensitive hard X-ray photoelectron spectroscopy. Materials Research Letters. 7(3). 117–123. 18 indexed citations
19.
Grossi, Alessandro, Eduardo Pérez, Cristian Zambelli, et al.. (2018). Impact of the precursor chemistry and process conditions on the cell-to-cell variability in 1T-1R based HfO2 RRAM devices. Scientific Reports. 8(1). 11160–11160. 33 indexed citations
20.
Niu, Gang, Matthias Auf der Maur, Francesco Santoni, et al.. (2016). Geometric conductive filament confinement by nanotips for resistive switching of HfO2-RRAM devices with high performance. Scientific Reports. 6(1). 25757–25757. 79 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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