World's Best Scientists 2026 revealed!
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Computer Science
Mexico
2026

D-Index & Metrics

Computer Science

D-Index
50
Citations
8430
World Ranking
5686
National Ranking
6

Research.com Recognitions

  • 2026 - Research.com Computer Science in Mexico Leader Award

Overview

Erik Cuevas is affiliated with the University of Guadalajara in Mexico and has a research focus primarily in computer science and engineering. Their work includes extensive contributions to artificial intelligence, computational theory and mathematics, as well as electrical and electronic engineering, with a significant publication record in these domains.

The main research fields Erik Cuevas has engaged with include:

  • Computer Science
  • Engineering

The subfields where their work is concentrated are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

The most frequent topics covered in their research are:

  • Metaheuristic Optimization Algorithms Research
  • Evolutionary Algorithms and Applications
  • Advanced Multi-Objective Optimization Algorithms
  • Scheduling and Optimization Algorithms
  • Image Enhancement Techniques
  • Image and Signal Denoising Methods
  • Cellular Automata and Applications

Erik Cuevas has authored papers in various prominent venues. The frequent publication outlets include:

  • Mathematics
  • IEEE Access
  • Mathematics and Computers in Simulation
  • Applied Soft Computing
  • Applied Mathematical Modelling

Recent notable papers authored by or co-authored with Erik Cuevas are:

  • An agent-based model to evaluate the COVID-19 transmission risks in facilities, 2020, Computers in Biology and Medicine
  • A better balance in metaheuristic algorithms: Does it exist?, 2020, Swarm and Evolutionary Computation
  • An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation, 2021, Knowledge-Based Systems
  • AltWOA: Altruistic Whale Optimization Algorithm for feature selection on microarray datasets, 2022, Computers in Biology and Medicine
  • Harris Hawks optimisation with Simulated Annealing as a deep feature selection method for screening of COVID-19 CT-scans, 2021, Applied Soft Computing

Erik Cuevas collaborates frequently with a network of co-authors, including:

  • Marco Pérez-Cisneros
  • Daniel Zaldívar
  • Alma Rodríguez
  • Héctor Escobar
  • Alberto Luque

In addition to journal publications, Erik Cuevas has contributed to academic book literature with multiple titles published primarily through Springer Nature and Morgan & Claypool Publishers. Some of these books include:

  • Metaheuristic Computation: A Performance Perspective
  • Metaheuristic Algorithms: New Methods, Evaluation, and Performance Analysis
  • Recent Metaheuristic Computation Schemes in Engineering
  • Analysis and Comparison of Metaheuristics
  • New Metaheuristic Schemes: Mechanisms and Applications
  • Advanced Metaheuristics: Novel Approaches for Complex Problem Solving
  • Optimization Strategies: A Decade of Metaheuristic Algorithm Development
  • DC Motors
  • Computational Methods with MATLAB®
  • Optimization in Industrial Engineering

Best Publications

  • A swarm optimization algorithm inspired in the behavior of the social-spider

    Erik Cuevas;Miguel Cienfuegos;Daniel ZaldíVar;Marco PéRez-Cisneros

  • Parameter identification of solar cells using artificial bee colony optimization

    Diego Oliva;Erik Cuevas;Gonzalo Pajares

  • A better balance in metaheuristic algorithms: Does it exist?

    Bernardo Morales-Castañeda;Daniel Zaldívar;Erik Cuevas;Fernando Fausto

  • An agent-based model to evaluate the COVID-19 transmission risks in facilities.

    Erik Cuevas

  • An optimization algorithm inspired by the States of Matter that improves the balance between exploration and exploitation

    Erik Cuevas;Alonso Echavarría;Marte A. Ramírez-Ortegón

  • Kalman filter for vision tracking

    Erik V. Cuevas;Daniel Zaldivar;Raúl Rojas

  • A comparison of nature inspired algorithms for multi-threshold image segmentation

    ValentıN Osuna-Enciso;Erik Cuevas;Humberto Sossa

  • Cross entropy based thresholding for magnetic resonance brain images using Crow Search Algorithm

    Diego Oliva;Salvador Hinojosa;Erik Cuevas;Gonzalo Pajares

  • A Multilevel Thresholding algorithm using electromagnetism optimization

    Diego Oliva;Erik Cuevas;Gonzalo Pajares;Daniel Zaldivar

  • From ants to whales: metaheuristics for all tastes

    Fernando Fausto;Adolfo Reyna-Orta;Erik Cuevas;Ángel G. Andrade

  • Multilevel Thresholding Segmentation Based on Harmony Search Optimization

    Diego Oliva;Erik Cuevas;Gonzalo Pajares;Daniel Zaldivar

  • A new algorithm inspired in the behavior of the social-spider for constrained optimization

    Erik Cuevas;Miguel Cienfuegos

  • A novel multi-threshold segmentation approach based on differential evolution optimization

    Erik Cuevas;Daniel Zaldivar;Marco Pérez-Cisneros

  • A global optimization algorithm inspired in the behavior of selfish herds.

    Fernando Fausto;Erik Cuevas;Arturo Valdivia;Adrián González

  • Circle detection using electro-magnetism optimization

    Erik Cuevas;Diego Oliva;Daniel Zaldivar;Marco Pérez-Cisneros

  • An improved opposition-based marine predators algorithm for global optimization and multilevel thresholding image segmentation

    Essam H. Houssein;Kashif Hussain;Laith Mohammad Abualigah;Laith Mohammad Abualigah;Mohamed E. Abd Elaziz

  • AltWOA: Altruistic Whale Optimization Algorithm for feature selection on microarray datasets

    Unknown

  • An Improved Crow Search Algorithm Applied to Energy Problems

    Primitivo Díaz;Marco Pérez-Cisneros;Erik Cuevas;Omar Avalos

  • A multi-level thresholding method for breast thermograms analysis using Dragonfly algorithm

    Margarita-Arimatea Díaz-Cortés;Noé Ortega-Sánchez;Salvador Hinojosa;Diego Oliva

  • A multi-threshold segmentation approach based on Artificial Bee Colony optimization

    Erik Cuevas;Felipe Sención;Daniel Zaldivar;Marco Pérez-Cisneros

  • Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC)

    Erik Cuevas;Daniel ZaldíVar;Marco PéRez-Cisneros;Humberto Sossa

Frequent Co-Authors

Marco Pérez-Cisneros
Marco Pérez-Cisneros University of Guadalajara
Diego Oliva
Diego Oliva University of Guadalajara
Raúl Rojas
Raúl Rojas Freie Universität Berlin
Gonzalo Pajares
Gonzalo Pajares Complutense University of Madrid
Mohamed Abd Elaziz
Mohamed Abd Elaziz Ajman University of Science and Technology
Ram Sarkar
Ram Sarkar Jadavpur University
Songfeng Lu
Songfeng Lu Huazhong University of Science and Technology
Ahmed A. Ewees
Ahmed A. Ewees Damietta University
Laith Mohammad Abualigah
Laith Mohammad Abualigah Al al-Bayt University

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