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Research

Current

My current postgraduate research explores the application of high performance computing (HPC) and machine learning (ML) methodologies to scientific problems, with a focus on areas like radiation schemes in climate prediction models.

Publications

Publications related to my postgraduate course. There is also a file containing the references in BibTeX format.

  • Miranda, E. F. (2022). Common MPI-based HPC Approaches in Python Evaluated for Selected Test Cases (Master’s Thesis, National Institute for Space Research - INPE). URI http://urlib.net/ibi/QABCDSTQQW/46C4U9H.
  • Miranda, E. F., & Stephany, S. (2022). Common MPI-Based Solutions for High-Performance Processing in Python Evaluated on Selected Test Cases [Presentation]. DOI 10.5281/zenodo.10676832.
  • Miranda, E. F., & Stephany, S. (2021). Comparison of High-performance Computing Approaches in the Python Environment for a Five-point Stencil Test Problem. XV Brazilian E-Science Workshop, at XLI Congress of the Brazilian Computer Society (CSBC-2021), 33–40. DOI 10.5753/bresci.2021.15786.
  • Miranda, E. F., & Stephany, S. (2021). Common HPC Approaches in Python Evaluated for a Scientific Computing Test Case. Revista Cereus, 13(2), 84–98. DOI 10.18605/2175-7275/cereus.v13n2p84-98.
  • Miranda, E. F., & Stephany, S. (2021). Comparison of high-performance computing approaches in the Python environment for a five-point stencil case study. XV Brazilian e-Science Workshop (BreSci), Online [Presentation]. DOI 10.5281/zenodo.10672456.

Manuscripts

Manuscripts related to my postgraduate course. There is also a file containing the references in BibTeX format.

  • Miranda, E. F., Santos, L. B. L., & Stephany, S. (2023). Data-Driven Parameter Discovery of a One-Dimensional Burgers’ Equation Using a Physics-Informed Neural Network [Manuscript]. DOI 10.5281/zenodo.10676770. [Online version].
  • Miranda, E. F. (2022). Solution of a One-Dimensional Viscous Burgers' Equation Using a Physics-Informed Neural Network and a Gaussian Quadrature Method [Manuscript]. DOI 10.5281/zenodo.10676900. [Online version].
  • Miranda, E. F. (2022). Comparison of CNN and MLP Artificial Neural Network Models for an Optical Character Recognition Test Case [Manuscript]. DOI 10.5281/zenodo.10676917.

Projects

I maintain a repository on Github with my open source projects that I have been developing over time for various purposes: https://github.com/efurlanm/ .

The current main research repository is: https://github.com/efurlanm/radnn/. The research also uses the LNCC supercomputer Santos Dumont under the project AMPEMI.


Last edited: 2025-04-27 23:31:43