Home › Entities › academia › M. Prezioso

M. Prezioso

Researcher / author (OpenAlex)
Person academia

Facts

2 properties
Instance of
human[2]
Affiliation
University of California, Santa Barbara, Institute of Nanostructured Materials, Institute for Microelectronics and Microsystemsas of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
🔖 Identifiers · 2
ORCID iD
0000-0002-3318-9132
OpenAlex ID
A5059442749as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded

Report an error or request removal Lineage (PROV-JSON)

📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 13
3-D Memristor Crossbars for Analog and Neuromorphic Computing Applications, Fast, energy-efficient, robust, and reproducible mixed-signal neuromorphic classifier based on embedded NOR flash memory technology, High-Performance Mixed-Signal Neurocomputing With Nanoscale Floating-Gate Memory Cell Arrays, Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits, Memory Technologies for Neural Networks, Memristor-based perceptron classifier: Increasing complexity and coping with imperfect hardware, Mixed-Signal Neuromorphic Inference Accelerators: Recent Results and Future Prospects, Modeling and implementation of firing-rate neuromorphic-network classifiers with bilayer Pt/Al2O3/TiO2−x/Pt Memristors +5 more
← Authored by 13
3-D Memristor Crossbars for Analog and Neuromorphic Computing Applications, Fast, energy-efficient, robust, and reproducible mixed-signal neuromorphic classifier based on embedded NOR flash memory technology, High-Performance Mixed-Signal Neurocomputing With Nanoscale Floating-Gate Memory Cell Arrays, Implementation of multilayer perceptron network with highly uniform passive memristive crossbar circuits, Memory Technologies for Neural Networks, Memristor-based perceptron classifier: Increasing complexity and coping with imperfect hardware, Mixed-Signal Neuromorphic Inference Accelerators: Recent Results and Future Prospects, Modeling and implementation of firing-rate neuromorphic-network classifiers with bilayer Pt/Al2O3/TiO2−x/Pt Memristors +5 more
Affiliated with 1
University of California, Santa Barbara
Press Enter · cited answer in seconds

Summary

M. Prezioso is a human[1].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). M. Prezioso. Retrieved October 24, 2026, from https://4ort.xyz/entity/m-prezioso
MLA “M. Prezioso.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 Oct. 2026, https://4ort.xyz/entity/m-prezioso.
BibTeX @misc{4ortxyz_m-prezioso_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{M. Prezioso}}, year = {2026}, url = {https://4ort.xyz/entity/m-prezioso}, note = {Accessed: 2026-10-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): M. Prezioso — https://4ort.xyz/entity/m-prezioso (retrieved 2026-10-24)

Canonical URL: https://4ort.xyz/entity/m-prezioso · Last refreshed: