Manuel Febrero
Professor at University of Santiago de Compostela (USC)
Coauthor of the R package “fda.usc devoted to functional data analysis, Full Professor of Statistics and Op. Res. in Spain since 2008 where he received the B.S. degree in Mathematics (1990) and his PhD in Statistics (1995). He has more than 50 publications in topics related with time series, bootstrap, spatial statistics, functional data, and on statistical methods applied to environmental control. He is the former head of the Department of Statistics, Mathematical Analysis and Optimization at the Faculty of Mathematics of the USC and academic coordinator of the PhD Interuniversity Program in Statistics and Op. Res. jointly organized by the universities of Santiago de Compostela, A Coruña and Vigo. He is also co-chair of the specialized group in Statistics for Functional Data of the group Computing & Statistics at ERCIM (European Research Consortium for Informatics and Mathematics).
Professor at University of Santiago de Compostela (USC)
Coauthor of the R package “fda.usc devoted to functional data analysis, Full Professor of Statistics and Op. Res. in Spain since 2008 where he received the B.S. degree in Mathematics (1990) and his PhD in Statistics (1995). He has more than 50 publications in topics related with time series, bootstrap, spatial statistics, functional data, and on statistical methods applied to environmental control. He is the former head of the Department of Statistics, Mathematical Analysis and Optimization at the Faculty of Mathematics of the USC and academic coordinator of the PhD Interuniversity Program in Statistics and Op. Res. jointly organized by the universities of Santiago de Compostela, A Coruña and Vigo. He is also co-chair of the specialized group in Statistics for Functional Data of the group Computing & Statistics at ERCIM (European Research Consortium for Informatics and Mathematics).
Variable Selection in Regression Models for Complex Data
A new algorithm for variable selection in regression models with scalar response is presented. This algorithm allows to combine the information of the covariates of different nature: functional, scalar, multivariate, categorical in a homogeneous way through the intensive use of distance correlation.
A new algorithm for variable selection in regression models with scalar response is presented. This algorithm allows to combine the information of the covariates of different nature: functional, scalar, multivariate, categorical in a homogeneous way through the intensive use of distance correlation.
Dean Attali
President & CEO at AttaliTech Ltd
Previously a software engineer at Google and top San Francisco startup Wish.com. Author of popular packages shinyjs (featured by RStudio), timevis, addinslist & more. Creator of “Shiny Case Studies” course — an interactive, online video course
President & CEO at AttaliTech Ltd
Previously a software engineer at Google and top San Francisco startup Wish.com. Author of popular packages shinyjs (featured by RStudio), timevis, addinslist & more. Creator of “Shiny Case Studies” course — an interactive, online video course
Will be set soon
Abbie Jones
Statistical Officer at Government Statistical Services, UK
Recently completed her PhD thesis “Associations between Socio-economic Factors and Stillbirth in Brazil and the UK” at Lancaster University. This thesis aimed, using routine national datasets, to determine the primary socio-economic risk factors associated with stillbirth in Brazil and the UK, and to compare relative magnitudes of these associations between and within the two countries. The project involved collaboration with UFF as part of the ESRC PhD Partnering Scheme.
Statistical Officer at Government Statistical Services, UK
Recently completed her PhD thesis “Associations between Socio-economic Factors and Stillbirth in Brazil and the UK” at Lancaster University. This thesis aimed, using routine national datasets, to determine the primary socio-economic risk factors associated with stillbirth in Brazil and the UK, and to compare relative magnitudes of these associations between and within the two countries. The project involved collaboration with UFF as part of the ESRC PhD Partnering Scheme.
Analysing an Aggregate Outcome as Binary Events with R, using Stillbirth Data from the PNAD
Joshua Kunst
Risk Analyst at Banco Falabella Chile
Data addict who enjoy the statistics, data science, programming and visualization. He likes share ideas and code. He lives in Santiago, Chile and is the author for the R wrapper for highcharts: highcharter.
Risk Analyst at Banco Falabella Chile
Data addict who enjoy the statistics, data science, programming and visualization. He likes share ideas and code. He lives in Santiago, Chile and is the author for the R wrapper for highcharts: highcharter.
Mission Imposible: Presenting highcharter and its best features in 30 minutes or less
Daniel Takata Gomes
Professor at ENCE/IBGE
Bacharel e mestre pela Unicamp e doutor em Estatística pela USP. Atualmente é professor e pesquisador na ENCE/IBGE. Atua na área de Probabilidade e Estatística, com ênfase em séries temporais, econometria, modelos lineares generalizados e teoria de valores extremos.
Professor at ENCE/IBGE
Bacharel e mestre pela Unicamp e doutor em Estatística pela USP. Atualmente é professor e pesquisador na ENCE/IBGE. Atua na área de Probabilidade e Estatística, com ênfase em séries temporais, econometria, modelos lineares generalizados e teoria de valores extremos.
Previsão através de deep learning e redes neurais LSTM: uma combinação insuperável
Karla Esquerre
Professor at UFBA
Dr. Karla Esquerre is the leader of the Growing with Applied Modeling and Multivariate Analysis research group (Gamma, www.gamma.ufba.br), which involves statistical and computational learning and data science in cooperative research projects with industries and in lecturing. She is the founder of R-Ladies Salvador and the coordinator of the Gender Diversity Project in Data Science: Training based on Experimentation, working with computational and statistical learning for 500 girl students in public schools. Dr. Esqueere has a PhD in Engenhara Química from UNICAMP, Brazil (2003), was postdoctoral fellow in Socio-Environmental Engineering at the University of Hokkaido (Japan, 2003-2005), and was a visiting Professor within the Department of Aerospace Mechanics, University of California, San Diego (2015-2016). She is currently an Associate Professor in the Department of Chemical Engineering and teacher and researcher in the Industrial Engineering Program (PEI) and Master in Environment, Water and Sanitation (MAASA) graduate programs at Federal University of Bahia.
Professor at UFBA
Dr. Karla Esquerre is the leader of the Growing with Applied Modeling and Multivariate Analysis research group (Gamma, www.gamma.ufba.br), which involves statistical and computational learning and data science in cooperative research projects with industries and in lecturing. She is the founder of R-Ladies Salvador and the coordinator of the Gender Diversity Project in Data Science: Training based on Experimentation, working with computational and statistical learning for 500 girl students in public schools. Dr. Esqueere has a PhD in Engenhara Química from UNICAMP, Brazil (2003), was postdoctoral fellow in Socio-Environmental Engineering at the University of Hokkaido (Japan, 2003-2005), and was a visiting Professor within the Department of Aerospace Mechanics, University of California, San Diego (2015-2016). She is currently an Associate Professor in the Department of Chemical Engineering and teacher and researcher in the Industrial Engineering Program (PEI) and Master in Environment, Water and Sanitation (MAASA) graduate programs at Federal University of Bahia.
Diversidade de Gênero na Ciência de Dados: Formação com Base na Experimentação
Fernando Almeida Barbalho
Federal Auditor at Secretaria do Tesouro Nacional (STN)
Doutor em Administração pela Universidade de Brasília (2014). Atualmente é auditor federal de finanças e controle da Secretaria do Tesouro Nacional (STN). Na STN atua como cientista de dados no Grupo Técnico de Comunicação Estratégica e Análise de Dados, utilizando o R como principal ferramenta de trabalho. A trajetória profissional e acadêmica mais recente está principalmente relacionada a dados abertos e desenvolvimento de produtos que resultem em maior transparência do Setor Público brasileiro. Participa de várias comunidades de prática que se formaram em torno do aplicativo de mensageria Telegram. Nos finais de semana costuma utilizar o R para investigar perguntas de pesquisa que escapam ao mundo das finanças públicas.
Federal Auditor at Secretaria do Tesouro Nacional (STN)
Doutor em Administração pela Universidade de Brasília (2014). Atualmente é auditor federal de finanças e controle da Secretaria do Tesouro Nacional (STN). Na STN atua como cientista de dados no Grupo Técnico de Comunicação Estratégica e Análise de Dados, utilizando o R como principal ferramenta de trabalho. A trajetória profissional e acadêmica mais recente está principalmente relacionada a dados abertos e desenvolvimento de produtos que resultem em maior transparência do Setor Público brasileiro. Participa de várias comunidades de prática que se formaram em torno do aplicativo de mensageria Telegram. Nos finais de semana costuma utilizar o R para investigar perguntas de pesquisa que escapam ao mundo das finanças públicas.
R, Python e Dados abertos no telegram: redes de colaboração por mais controle social
Julio Trecenti
President at CONRE-3a Região
Considera-se um Faxineiro de Dados. Sócio-fundador da Curso-R. Doutorando em Estatística pelo IME-USP. Secretário-geral da Associação Brasileira de Jurimetria (ABJ). Sócio-fundador da Terranova Consultoria. Trabalha com web scraping, arrumação de dados, construção de modelos preditivos, APIs, pacotes em R e dashboards em Shiny. Coordenador e ministrante de diversos cursos sobre R, ciência de dados e jurimetria.
President at CONRE-3a Região
Considera-se um Faxineiro de Dados. Sócio-fundador da Curso-R. Doutorando em Estatística pelo IME-USP. Secretário-geral da Associação Brasileira de Jurimetria (ABJ). Sócio-fundador da Terranova Consultoria. Trabalha com web scraping, arrumação de dados, construção de modelos preditivos, APIs, pacotes em R e dashboards em Shiny. Coordenador e ministrante de diversos cursos sobre R, ciência de dados e jurimetria.
Resolvendo CAPTCHAs com o pacote decryptr
Bruna Wundervald
Ph.D. Candidate in Bayesian Machine Learning & R-Ladies Co-organiser
Bruna is a Ph.D. candidate in Bayesian Machine Learning at the Hamilton Institute, in the National University of Ireland Maynooth. Member and co-organiser of the Curitiba and São Paulo R-Ladies chapters in Brazil, also involved with the worldwide community. Founder and developer of the R-Music organization, that promotes the study of music information retrieval in R. Previously, she obtained her BSc in Statistics at the Paraná Federal University, where she worked in a diversity of extension projects involving R and statistics. Interested in ML in general, package and dashboards building, text mining and APIs. Her work is now especially focused on the development of new methods for Bayesian machine learning using both R and python, as well as multivariate statistics, variational inference, and MIR.
Ph.D. Candidate in Bayesian Machine Learning & R-Ladies Co-organiser
Bruna is a Ph.D. candidate in Bayesian Machine Learning at the Hamilton Institute, in the National University of Ireland Maynooth. Member and co-organiser of the Curitiba and São Paulo R-Ladies chapters in Brazil, also involved with the worldwide community. Founder and developer of the R-Music organization, that promotes the study of music information retrieval in R. Previously, she obtained her BSc in Statistics at the Paraná Federal University, where she worked in a diversity of extension projects involving R and statistics. Interested in ML in general, package and dashboards building, text mining and APIs. Her work is now especially focused on the development of new methods for Bayesian machine learning using both R and python, as well as multivariate statistics, variational inference, and MIR.
Probabilistic Graphical Models in R and Python
Letícia Rosa
Student at Instituto Nacional de Pesquisas Espaciais (INPE)
Graduanda em Ciência da Computação e estudante de iniciação científica aplicada à Data Science no INPE. É colaboradora científica no IEAv e organizadora do PyLadies e Django Girls de São José dos Campos.
Student at Instituto Nacional de Pesquisas Espaciais (INPE)
Graduanda em Ciência da Computação e estudante de iniciação científica aplicada à Data Science no INPE. É colaboradora científica no IEAv e organizadora do PyLadies e Django Girls de São José dos Campos.
Plotly R em 20 minutos
