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Fernanda Eustáquio
Master in Computer Science from the Department of Computer Science at Federal University of Bahia (UFBA). Since her undergraduate education in Computer Science at UFBA (2017), she researches unsupervised machine learning, fuzzy clustering (fuzzy c-means) and validation (internal clustering validity indices) of high-dimensional datasets.
Education
BSc in Computer Science
Federal University of Bahia (UFBA)
Salvador, Brazil
2012 - 2017
Thesis: Um estudo sobre índices de validação de agrupamento fuzzy para dados de alta dimensionalidade (https://repositorio.ufba.br/ri/handle/ri/24355)
MSc Degree in Computer Science - Computational Intelligence
Federal University of Bahia (UFBA)
Salvador, Brazil
2017 - 2020
Thesis: On Fuzzy Cluster Validity Indices For Soft Subspace Clustering Of High-Dimensional Datasets (http://repositorio.ufba.br/ri/handle/ri/33507)
Research Experience
Scholarship, Functional Placement: Exclusive Dedication - Fundação de Amparo à Pesquisa do Estado da Bahia, FAPESB
Federal University of Bahia (UFBA), Computer Science Department
Salvador, Brazil
2015 - 2016
Scholarship, Functional Placement: Exclusive Dedication - Coordination for the Improvement of Higher Education Personnel, CAPES
Federal University of Bahia (UFBA), Computer Science Department
Salvador, Brazil
2018 - 2019
Professional Experience
Data Curation Assistant - Type of contract: scholarship holder
Centro de Integração de Dados e Conhecimentos para Saúde (CIDACS) - Oswaldo Cruz Foundation
Salvador, Brazil
2020 - 2021
- Data quality.
- Write HTML data statistical descriptions.
- Data inspection.
- Health data.
- Anonymization.
Reviewer Experience
Reviewer in some journals and conferences
Journal of Applied Bioinformatics & Computational Biology, International Journal of Electrical and Computer Engineering certificate and Encontro Nacional de Inteligência Artificial e Computacional (ENIAC).
N/A
2019 - 2020
Selected Publications and Posters
Evaluating the numerical instability in fuzzy clustering validation of high-dimensional data.
EUSTAQUIO, F. and NOGUEIRA, T. Theoretical Computer Science, vol. 805, pp. 19 - 36. doi.org/evaluating
N/A
2020
[dataset] Gaussian Mixture high-dimensional datasets.
EUSTAQUIO, F. Mendeley Data, V1. doi.org/gaussian
N/A
2020
On Monotonic Tendency of Some Fuzzy Cluster Validity Indices for High-Dimensional Data.
EUSTAQUIO, F. and NOGUEIRA, T. 7th Brazilian Conference on Intelligent Systems (BRACIS), pp. 558-563. doi.org/monotonic
São Paulo, Brazil
2018
On Fuzzy Cluster Validity Indexes for High Dimensional Feature Space.
EUSTAQUIO, F., NOGUEIRA, T., CAMARGO, H., and REZENDE, S. Springer International Publishing, pp. 12 - 23. doi.org/fuzzycluster
N/A
2017
Influência de Técnicas Não-supervisionadas de Redução de Dimensionalidade para Organização Flexível de Documentos (The Unsupervised Dimensionality Reduction Weight on Flexible Document Organization).
LIMA, B., EUSTAQUIO, F., and NOGUEIRA, T. Proceedings of the 11th Brazilian Symposium in Information and Human Language Technology (STIL), pp. 112 - 121. URL
Uberlância, Brazil
2017
Certificates and Worshops
English extension course (Workload: 360h)
Promoted by the Núcleo Permanente de Extensão em Letras (NUPEL) of Federal University of Bahia certificate
Salvador, Brazil
2017
Languages
Awards
Destaque pelo subcomitê de Ciências Exatas e da Terra
No programa PIBIC 2015/2016, Coordenação de Iniciação à Pesquisa, Criação e Inovação. (https://drive.google.com/file/d/1L6-NIyM09KcKla3hB272RQZfsdAMrAqB/view?usp=sharing)
Salvador, Brazil
2015