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Ministério da Defesa (Brasil). Instituto Tecnológico de Aeronáutica (ITA). Divisão de Ciência da Computação (IEC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
Medical Physicist from the Federal University of Health Sciences of Porto Alegre (UFCSPA). Master in Data Science from the Graduate Program in Operations Research (PPG-PO) at the Federal University of São Paulo (UNIFESP) and the Technological Institute of Aeronautics (ITA), funded by FAPESP. During the master's program, he was a visiting researcher at the University of Coimbra through the FAPESP's Research Internship Abroad (BEPE) scholarship, for six months. Currently, he is a Ph.D. student in the PPG-PO program, focusing on Data-Centric AI and Missing Data. (Source: Lattes Curriculum)
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Real-world data often present challenges such as imbalance, noise, and missing values. Recently, the Machine Learning literature has demonstrated that improving model performance also requires enhancing the quality of the data used for training, giving rise to a new research field known as Data-Centric Artificial Intelligence. Missing values, defined as the absence of information in one o…
Various issues can deteriorate data quality in Machine Learning. Among them, one may cite the quality of the features, which can be impaired by the presence of noise and missing data. Noise can be inputted in data in several steps during data collection, storage and transmission. In supervised problems, they can be present both in the labels and in the predictive input features. Missing v…
Various issues can deteriorate data quality in Machine Learning. Among them, one may cite the quality of the input features, which can be impaired by the presence of noise and missing data. Noise can be inputted into data in several steps during collection, storage, and transmission. In supervised problems, they can be present both in the labels and in the predictive input features. Missi…
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