Miguel Méndez-Garabetti

About

Telecommunications Engineer (Universidad del Aconcagua). Master in Information Technology (Universidad de León, Spain). PhD in Computer Science from the National University of San Luis. Research related to the improvement of quality and performance in prediction systems through high-performance computing, metaheuristics and bio-inspired algorithms. Professor at different universities in the country. Director of the Master's Degree in Teleinformatics at the University of Mendoza. Founder of the Free and Open Source Software and Hardware Research Laboratory (FOSSHLab).

Employment

• Universidad Nacional de San Juan Researcher
  2026 - Present
• Universidad Católica de Salta Independent Researcher
  2023 - Present
• Universidad Nacional de Cuyo Professor
  2022 - Present

Education

• Universidad Nacional de la Plata Posdoctorado
  2025 - Present
• Universidad Nacional de San Luis PhD in Computer Science
  2012 - 2020
• Universidad de León MSc in Information Technology
  2011 - 2013
• Universidad del Aconcagua BSc Telecommunication Engineering
  2006 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (7)

• HESS-IM: A Uncertainty Reduction Method that Integrates Remote Sensing Data Applied to Forest Fire Behavior Prediction
  2021 DOI: 10.1007/978-3-030-84825-5_2
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• Dynamic Tuning of a Forest Fire Prediction Parallel Method
  2020 DOI: 10.1007/978-3-030-48325-8_2
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• Hierarchical parallel model for improving performance on differential evolution
  Concurrency and Computation: Practice and Experience 2017 DOI: 10.1002/cpe.4087
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• A comparative study of evolutionary statistical methods for uncertainty reduction in forest fire propagation prediction
  Procedia Computer Science 2017 DOI: 10.1016/j.procs.2017.05.252
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• Increase in the quality of the prediction of a computational wildfire behavior method through the improvement of the internal metaheuristic
  Fire Safety Journal 2016 DOI: 10.1016/j.firesaf.2016.03.002
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• Comparative Analysis of Performance and Quality of Prediction Between ESS and ESS-IM
  Electronic Notes in Theoretical Computer Science 2015 DOI: 10.1016/j.entcs.2015.05.004
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• Evolutionary-Statistical System: A parallel method for improving forest fire spread prediction
  Journal of Computational Science 2015 DOI: 10.1016/j.jocs.2014.12.001
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