World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
5330
World Ranking
12584
National Ranking
799

Overview

Isaac Triguero is affiliated with the University of Nottingham in the United Kingdom. Their research primarily spans the field of Computer Science, with a particular focus on Artificial Intelligence. The scientist's work also intersects with other subfields including Electrical and Electronic Engineering, Pulmonary and Respiratory Medicine, Signal Processing, and Management Science and Operations Research.

The main research topics Isaac Triguero has contributed to are diverse, reflecting a broad spectrum within AI and data science. These include:

  • Machine Learning and Data Classification
  • Data Stream Mining Techniques
  • Explainable Artificial Intelligence (XAI)
  • Domain Adaptation and Few-Shot Learning
  • Species Distribution and Climate Change
  • Time Series Analysis and Forecasting
  • Energy Load and Power Forecasting

Isaac Triguero's recent publications demonstrate this thematic range. Examples include:

  • "Multigranulation Supertrust Model for Attribute Reduction" published in 2020 in IEEE Transactions on Fuzzy Systems
  • "General Purpose Artificial Intelligence Systems (GPAIS): Properties, definition, taxonomy, societal implications and responsible governance" published in 2023 in Information Fusion
  • "Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort" published in 2022 in The Lancet Digital Health
  • "Redundancy and Complexity Metrics for Big Data Classification: Towards Smart Data" published in 2020 in IEEE Access
  • "EUSC: A clustering-based surrogate model to accelerate evolutionary undersampling in imbalanced classification" published in 2020 in Applied Soft Computing

The scientist has also contributed to book publications, notably a title published by Cambridge University Press entitled "Large-Scale Data Analytics with Python and Spark" in 2023.

Isaac Triguero frequently collaborates with several colleagues in their research endeavors. Some of the most frequent coauthors are:

  • Mikel Galar
  • Francisco Herrera
  • Salvador García
  • Direnc Pekaslan
  • Daniel Molina

Their work is commonly published in venues such as:

  • arXiv (Cornell University)
  • IEEE Access
  • Information Fusion
  • Information Sciences
  • Applied Intelligence

This profile summarizes Isaac Triguero's contributions in terms of research areas, collaborations, and publication outlets, illustrating a multidisciplinary approach within the wider domain of Computer Science and Artificial Intelligence.

Best Publications

  • Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

    Isaac Triguero;Salvador García;Francisco Herrera

  • Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study

    Mikel Canizo;Isaac Triguero;Angel Conde;Enrique Onieva

  • A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification

    I. Triguero;J. Derrac;S. Garcia;F. Herrera

  • KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

    Isaac Triguero;Sergio González;Jose M. Moyano;Salvador García

  • kNN-IS

    Jesus Maillo;Sergio Ramírez;Isaac Triguero;Francisco Herrera

  • MRPR: A MapReduce solution for prototype reduction in big data classification

    Isaac Triguero;Daniel Peralta;Jaume Bacardit;Salvador García

  • Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data

    Isaac Triguero;Diego García-Gil;Jesús Maillo;Julián Luengo

  • Evolutionary-based selection of generalized instances for imbalanced classification

    Salvador Garcıa;Joaquın Derrac;Isaac Triguero;Cristóbal J. Carmona

  • A survey on fingerprint minutiae-based local matching for verification and identification

    Daniel Peralta;Mikel Galar;Isaac Triguero;Daniel Paternain

  • Evolutionary Feature Selection for Big Data Classification: A MapReduce Approach

    Daniel Peralta;Sara del Río;Sergio Ramírez-Gallego;Isaac Triguero

  • Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification

    Isaac Triguero;Salvador García;Francisco Herrera

  • ROSEFW-RF

    Isaac Triguero;Sara del Río;Victoria López;Jaume Bacardit

  • On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification

    Isaac Triguero;José A. Sáez;Julián Luengo;Salvador García

  • On the use of convolutional neural networks for robust classification of multiple fingerprint captures

    Daniel Peralta;Isaac Triguero;Salvador García;Yvan Saeys

  • Fast fingerprint identification for large databases

    D. Peralta;I. Triguero;R. Sanchez-Reillo;F. Herrera

  • A review on the self and dual interactions between machine learning and optimisation

    Heda Song;Isaac Triguero;Ender Özcan

  • SEG-SSC: A Framework Based on Synthetic Examples Generation for Self-Labeled Semi-Supervised Classification

    Isaac Triguero;Salvador Garcia;Francisco Herrera

  • A MapReduce-Based k-Nearest Neighbor Approach for Big Data Classification

    Jesus Maillo;Isaac Triguero;Francisco Herrera

  • A survey of fingerprint classification Part II

    Mikel Galar;Joaquín Derrac;Daniel Peralta;Isaac Triguero

  • A MapReduce-Based k-Nearest Neighbor Approach for Big Data Classification

    Unknown

  • Evolutionary undersampling for extremely imbalanced big data classification under apache spark

    I. Triguero;M. Galar;D. Merino;J. Maillo

  • Integrating Instance Selection, Instance Weighting, and Feature Weighting for Nearest Neighbor Classifiers by Coevolutionary Algorithms

    J. Derrac;I. Triguero;S. Garcia;F. Herrera

Frequent Co-Authors

Francisco Herrera
Francisco Herrera University of Granada
Salvador García
Salvador García University of Granada
José Manuel Benítez
José Manuel Benítez University of Granada
Mikel Galar
Mikel Galar Universidad Publica De Navarra
Robert John
Robert John University of Nottingham
Humberto Bustince
Humberto Bustince Universidad Publica De Navarra
Julián Luengo
Julián Luengo University of Granada
Yvan Saeys
Yvan Saeys Ghent University
Ender Özcan
Ender Özcan University of Nottingham
Weiping Ding
Weiping Ding Nantong University

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