Alejandro Maté

Associate professor

Universidad de Alicante

Spain

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About

Alejandro Maté is an Associate Professor at the University of Alicante, Spain. His research focuses on areas including Industry 4.0, machine learning, and the analysis of mental disorders using EEG. Recent publications include work on storytelling dashboards, ADHD diagnosis refinement, and interpretable models for predicting COVID-19 patient outcomes.

Articles (19)

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2025

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2020

Collaborators (5)

Miguel Ángel Teruel Martínez

Adjunct Professor

Universidad de Alicante

SPAIN

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Pedro Guimarães

Invited Assistant Professor

University of Minho

PORTUGAL

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Maria del Mar Roldan-Garcia

Profesor Contratado Doctor

University of Malaga

SPAIN

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Carlos Blanco

Phd Assistant Professor

Universidad de Cantabria

SPAIN

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Maribel Yasmina Santos

Full Professor

University of Minho

PORTUGAL

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Alejandro Maté

Research Interests

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About

Articles (19)

A methodology for the systematic design of storytelling dashboards applied to Industry 4.0

An extension of iStar for Machine Learning requirements by following the PRISE methodology

An extension of iStar for Machine Learning requirements by following the PRISE methodology

An ontology-based secure design framework for graph-based databases

Refining ADHD diagnosis with EEG: The impact of preprocessing and temporal segmentation on classification accuracy

Feature engineering of EEG applied to mental disorders: a systematic mapping study

A Data Analytics Methodology to Visually Analyze the Impact of Bias and Rebalancing

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers

Beyond TPC-DS, a benchmark for Big Data OLAP systems (BDOLAP-Bench)

Beyond TPC-DS, a benchmark for Big Data OLAP systems (BDOLAP-Bench)

Fault detection and diagnosis for industrial processes based on clustering and autoencoders: a case of gas turbines

A methodology to automatically translate user requirements into visualizations: Experimental validation

A New Big Data Benchmark for OLAP Cube Design Using Data Pre-Aggregation Techniques

Solar Energy Prediction Model Based on Artificial Neural Networks and Open Data

Fostering Sustainability through Visualization Techniques for Real-Time IoT Data: A Case Study Based on Gas Turbines for Electricity Production

Improving Sustainability of Smart Cities through Visualization Techniques for Big Data from IoT Devices

An Iterative Methodology for Defining Big Data Analytics Architectures

An Iterative Methodology for Defining Big Data Analytics Architectures

Collaborators (5)

Miguel Ángel Teruel Martínez

Pedro Guimarães

Maria del Mar Roldan-Garcia

Carlos Blanco

Maribel Yasmina Santos

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