CV Lattes
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Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC) (Institutional affiliation from the last research proposal) Birthplace: Brazil
B.Sc in in Applied Mathematics and Scientific Computing from Universidade de São Paulo (2004), Masters degree in Computer Science and Computational Mathematics from Universidade de São Paulo (2006) and PhD in Statistics from Universidade de São Paulo (2010). She earned her Habilitation (Livre-docência) at USP (2025). Teaches currently at the Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo in São Carlos, SP Brazil. She is an Assistant Professor in Statistics and Data Science, has experience in regression Models, working mainly in the following topics: nonlinear models, elliptical models, mixed-effects models, diagnosis of influence, validation of models, models with errors in variables, latent variables models, item response theory. She was a visitor researcher at the Erasmus Medical Center in Rotterdam, The Netherlands, in 2013-2014. She was the coordinator of the Bachelors degree in Estatística e Ciência de Dados at ICMC USP from 2018 to 2022 and supervises Ph.D., Masters, undergraduate research, graduation projects, and specialization students. She is a professor and advisor in the MBA em Ciências de Dados at CeMEAI ICMC USP and in the MBA em Inteligência Artificial e Big Data at ICMC. She is the deputy coordinator of the Estatística e Otimização para Ciência de Dados e Pesquisa Operacional (CDPO) course at ICMC USP. Has more than 530 citations and h-index 10 according to scholar google http://scholar.google.com.br/citations?user=nGGeov8AAAAJhl=pt-BR . She is the mother of two children and was on maternity leave in 2016 and 2019. (Source: Lattes Curriculum)
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In this project we propose the investigation of important issues related to the nonlinear mixed-effects modeling assuming elliptical errors, including the assumption of heteroscedastic and/or autoregressive structures as a generalization of the scale matrix from the models developed by the applicant Cibele Russo in her Doctorate Thesis and published in Computational Statistics and Data An…
In this project we discuss the development and analysis of nonlinear elliptical models, which represents a new methodology for obtaining robust estimates to nonlinear correlated data. The nonlinear models have been widely used, but little can be found using the elliptical approach. We intend to consider models which were previously analysed under normality, but that presented heavy tail w…
The importance of mixed-effects models is unquestionable for problems with correlated data, as longitudinal data or repeated measurements. Linear mixed-effects models have been extensively studied with a rich literature as a result. Also, generalized linear mixed models have been investigated quite intensively. However, non-linear mixed models, essential in areas as pharmacokinetics, grow…
| 1 / 1 | Completed research grants |
| 4 / 2 | Completed scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
| 6 / 4 | All research grants and scholarships |
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