International Conference on Robust Statistics 2017

Keynote Speakers

Irène Gijbels

Irène Gijbels (University of Leuven)

Abstract: Quantile regression in varying coefficient models

Irène Gijbels is Full Professor in Statistics at the Mathematics Department at the KU Leuven in Belgium. After receiving a PhD degree in Sciences (Statistics), she was a Visiting Professor at the University of North Carolina, Chapel Hill, USA (Fullbright-Hays scholarship), a Senior Research Assistant at the National Science Foundation (Belgium), and Professor at the Université catholique de Louvain, Louvain-la-Neuve (Belgium). At the KU Leuven she runs a successful and dynamic research group in mathematical statistics. Dr Gijbels is an expert in semi-and nonparametric methods, with currently a strong emphasis on flexible regression modelling (including heterogeneity, dispersion modelling, mean and quantile regression, flexible modelling for longtitudinal and functional data), as well as on the study of copula-based dependencies. She is co-author of the 1996 book on “Local Polynomial Modelling and Its Applications”, together with J. Fan.

She served/serves on various international scientific boards/committees, such as committees of the Institute of Mathematical Statistics (IMS), among others. She is the past Editor of Journal of Nonparametric Statistics and served/serves on the Editorial Boards of several major international scientific journals. For her contributions to statistics and her services to the international statistics community, she was awarded as a Fellow of the Institute of Mathematical Statistics and of the American Statistical Association. She is an elected member of the International Statistical Institute, and member of the Belgian Royal Academy of Sciences.

Graciela

Graciela Boente (University of Buenos Aires)

Abstract: Robust inference in functional data analysis

Professor Graciela Boente research has primarily focused in Robust Statistics, Nonparametric and Semiparametric Inference. She has developed robust procedures in nonparametric regression and autoregression models, partly linear and generalized partly linear models as well as in multivariate statistics and more recently, in functional data analysis.

She has a Full Professor with permanent position at the University of Buenos Aires and she has attained the highest possition at the CONICET, which is the National Research Council of Argentina.

She is a Fellow of the Institute of Mathematical Statistics. She has also been awarded with a Fellowship from the John Simon Memorial Foundation in 2002 and received in 2008 an Award from the National Academy of Exact, Physical and Natural Sciences in Argentina. She is Associate Editor of Computational Statistics and Data Analysis and Revstat and was Associate Editor of Statistica Sinica.

Noel Cressie-photo_Jun2014

Noel Cressie (University of Wollongong)

Abstract: Robust statistical methods in the geosciences

Noel Cressie is a Distinguished Professor and Director, Centre for Environmental Informatics, at the University of Wollongong in Wollongong, Australia. He is best known for having brought disparate statistical methodologies into a nascent discipline known as Spatial Statistics. Cressie was trained in Australia and the USA and obtained his Ph.D. in Statistics from Princeton University, USA, advised by Geoffrey Watson and taught by both Watson and John Tukey. He has spent the majority of his professional life in the USA as professor and distinguished professor at both Iowa State University and The Ohio State University. Since 2012, he has been professor and distinguished professor at the University of Wollongong, Australia.

His book, “Statistics for Spatio-Temporal Data” (2011), by Noel Cressie and Christopher K. Wikle, received two awards: the 2011 PROSE Award in the Mathematics category (for PROfessional and Scholarly Excellence, given by the Association of American Publishers); and the 2013 DeGroot Book Prize (awarded every two years by the International Society for Bayesian Analysis). More recently, Cressie was awarded the Pitman Medal in 2014 by the Statistical Society of Australia in recognition of his outstanding achievement in, and contribution to, the discipline of Statistics. In 2016, he received the Barnett Award by the Royal Statistical Society for excellence in environmental statistics. He was selected to deliver the Georges Matheron Lecture in 2017 by the International Association for Mathematical Geosciences.

Ray Chambers

Ray Chambers (University of Wollongong)

Abstract: Robust Models for Small Area Estimation - Random Group Effects vs. Random Group Indexing

Ray Chambers is Professorial Fellow at the National Institute for Applied Statistics Research Australia, University of Wollongong, Australia. He completed his PhD in Biostatistics at the Johns Hopkins University, Baltimore USA, in 1982. His research interests include sample survey design and analysis, robust statistical methods and statistical modelling and inference, with a particular focus on likelihood-based approaches, small area estimation, inference for linked data, M-quantile methods for group heterogeneity, spatial modelling as well as nonparametric and semiparametric methods. He is co-Editor in Chief of the International Statistical Review, an elected member of the International Statistical Institute and a Fellow of the American Statistical Association. He was President of the International Association of Survey Statisticians, 2011 - 2013, and International Representative on the Board of the American Statistical Association, 2010 - 2013.

Last reviewed: 16 June, 2017