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Filipa Barros is a computer science doctoral student at the University of Porto. Her MSc thesis had the title: Initial Condition Estimation in Flux Tube Simulations using Machine Learning and is expanding a similar theme in her Ph.D. She is also an invited lecturer at the Faculty of Engineering of the University of Porto currently lecturing a data structures and algorithms' class. Her main interests are Machine Learning applicability to space-related problems.
Identificação

Identificação pessoal

Nome completo
Ana Filipa Sousa Barros

Nomes de citação

  • S. Barros, Filipa

Identificadores de autor

Ciência ID
7717-30BD-8364
ORCID iD
0000-0002-9529-4990

Endereços de correio eletrónico

  • f.barros@fe.up.pt (Professional)

Domínios de atuação

  • Exact Sciences - Computer and Information Sciences

Idiomas

Idioma Conversação Leitura Escrita Compreensão Peer-review
Portuguese (Idioma materno)
English Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2) Proficiency (C2)
French Intermediate (B1) Intermediate (B1) Intermediate (B1) Elementary (A2) Intermediate (B1)
Formação
Grau Classificação
2021/09/01 - 2025
Ongoing
 Doctor's degree in Computer Science (Doutoramento)
Universidade do Porto Faculdade de Ciências, Portugal
2022/07 - 2022/08
Concluded
 Space Studies Program (Outros)
International Space University, France
2015/09/01 - 2021/07/30
Concluded
 Master in Electrical and Computer Engineering (Mestrado integrado)
Universidade do Porto Faculdade de Engenharia, Portugal
"Initial Condition Estimation in Flux Tube Simulations using Machine Learning" (TESE/DISSERTAÇÃO)
Produções

Publications

Book chapter
  1. Filipa S.Barros; Vitor Cerqueira; Carlos Soares. "Empirical Study on the Impact of Different Sets of Parameters of Gradient Boosting Algorithms for Time-Series Forecasting with LightGBM". 454-465. Springer International Publishing, 2021.
    10.1007/978-3-030-89188-6_34
Conference paper
  1. Nuno Costa; Filipa S. Barros; João J. G. Lima; Rui F. Pinto; André Restivo. "Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models". 2024.
    10.14428/esann/2024.es2024-110
Journal article
  1. Filipa S.Barros; Paula Graça; J.J.G. Lima; Rui Ferreira Pinto; Andre Restivo; Murillo Villa. "Using Recurrent Neural Networks to improve initial conditions for a solar wind forecasting model". Engineering Applications of Artificial Intelligence (2024): http://dx.doi.org/10.1016/j.engappai.2024.108266.
    10.1016/j.engappai.2024.108266
Preprint
  1. Filipa Barros; João José Graça Lima; Rui F. Pinto; André Restivo. "Neural Networks for Surrogate Models of the Corona and Solar Wind". 2025. https://doi.org/10.5194/egusphere-egu24-420.
    10.5194/egusphere-egu24-420
Report
  1. Stein Haaland; Filipa Barros; Lindis Merete Bjoland; Mikkel Breedveld. 2025. Secular shift of the magnetic dip pole and its consequences for auroral boundaries (PoleMotion). https://zenodo.org/doi/10.5281/zenodo.14425295.
    10.5281/ZENODO.14425295
Thesis / Dissertation
  1. Barros, Filipa. "Initial Condition Estimation in Flux Tube Simulations using Machine Learning". 2021.
Atividades

Supervision

Título / Tema
Papel desempenhado 		Curso (Tipo)
Instituição / Organização
2023/09 - 2024/07 Leveraging Physics-Informed Neural Operators for Solar Weather Modeling
Co-supervisor
 Informatics and Computing Engineering (Master)
Universidade do Porto Faculdade de Engenharia, Portugal
2022/09 - 2023/07 Enhancing ML Models for Solar Weather Forecasting using Clustering and Adversarial Anomaly Detection
Co-supervisor
 Informatics and Computing Engineering (Master)
Universidade do Porto Faculdade de Engenharia, Portugal

Event organisation

Nome do evento
Tipo de evento (Tipo de participação) 		Instituição / Organização
2023 - Atual 19th European Space Weather Week (ESWW 2023) - Part of the LOC (2023/11/20 - 2024/11/24)
Conference (Co-organisor)

Course / Discipline taught

Disciplina Curso (Tipo) Instituição / Organização
2022/02 - 2025/08 Data Structures and Algorithms electrical and computers' engineering (Licenciatura) Universidade do Porto Faculdade de Engenharia, Portugal
2021/09 - 2022/02 Computers’ Architecture Electrical and Computer Engineering (Mestrado integrado) Universidade do Porto Faculdade de Engenharia, Portugal