Massey University, New Zealand
Distinguished Professor Marti J. Anderson is an ecological statistician whose work spans several disciplines, from ecology to mathematical statistics. A Fellow of the Royal Society of New Zealand, and a recent recipient of a prestigious James Cook Fellowship, she holds the Professorial Chair in Statistics in the New Zealand Institute for Advanced Study (NZIAS) at Massey University in Auckland. Her core research is in community ecology, biodiversity, multivariate analysis, models of ecological count data, experimental design and resampling methods, with a special focus on creating new applied statistics for ecology that can yield new insights into global patterns of biodiversity. Marti is also the Director of PRIMER-e (Quest Researcher Limited), a boutique research and software development company that creates user-friendly software (PRIMER and PERMANOVA+) to implement robust multivariate statistical methods for ecological analysis and synthesis.
Wageningen University, Netherlands
Daniela Bustos-Korts works as a researcher at Biometris, Wageningen University (NL). She graduated with a BSc in Agriculture and an MSc in Crop Physiology from the Universidad Austral de Chile. In 2017, she obtained her PhD from Wageningen University. Her PhD thesis was about the use of statistical and crop growth models for phenotype prediction across multiple environments. Her research interests are in the development of strategies that combine statistical and crop growth models to help breeders designing effective phenotyping and prediction schemes that will help them improving response to selection. These strategies involve the use of crop growth models like APSIM and linear mixed models for multi-trait and multi-environment genomic prediction.
London School of Hygiene & Tropical Medicine, UK
James Carpenter is professor of medical statistics at the London School of Hygiene & Tropical Medicine, and has a 50% secondment to the MRC Clinical Trials Unit at UCL. Research interests include: missing observations (both outcomes and covariates), in particular the method of multiple imputation and sensitivity analysis; meta-analysis; multilevel modelling and bootstrap methods, with social and medical applications.
Technical University of Munich, Germany
The research activities of Professor Claudia Czado are in statistics. Her special interests lie in the modeling of complex dependencies including regression effects and time/space structures. For this she uses a copula approach and especially the flexible class of vine copulas. This allows for different non-symmetric dependencies for pairs of variables. For model selection and estimation in high dimensions computer-aided methods are developed. Applications are in finance, insurance and engineering.
After studying mathematics in Göttingen, Germany, Professor Claudia Czado obtained her doctorate in 1989 at Cornell University, USA, in Operations Research and Industrial Engineering. She then became an Assistant Professor and 1995 Associate Professor of Statistics at York University, Toronto, Canada. In 1998 she was appointed to the Technical University of Munich, Germany, in the field of Applied Mathematical Statistics. Professor Claudia Czado is the author or co-author of more than 120 publications. She is also co-founder/coordinator of the junior research program “Global Challenges for Women in Math Science” at the Technical University of Munich.
CSIRO & SAGI-North/DAF, Australia
Dr Joanne De Faveri is an applied statistician with interest in the application of statistical methods to agricultural research, especially plant breeding. She has worked most of her career in the Department of Agriculture and Fisheries as a Biometrician in Far North Queensland working with Horticulture breeding programs such as strawberry, pineapple, macadamia, mango and citrus. More recently she joined CSIRO as part of SAGI-North, the Statistics for the Australian Grains Industry project, where she develops and applies statistical methods to GRDC funded grains projects. She completed her PhD at the University of Adelaide in “Spatial and Temporal Modelling for Perennial Crop Variety Selection Trials” and has research interests in Linear Mixed Models, spatio-temporal modelling in field trials, statistical genetics and more recently statistics for High Throughput Phenomics (HTP). Currently she is most interested in developing statistical methodology to best integrate HTP (including aerial image, sensor and hyperspectral) data into crop breeding programs for better variety predictions. She enjoys the collaborative side of statistics in agriculture and applying new ideas to get the most out of research data.
Registry of Older South Australians, Australia
Max obtained his PhD in computational statistics from the University of Melbourne in 2008, with his doctoral thesis dedicated to the design and implementation of novel exact inference procedures. Being passionate about identifying hidden functional patterns contained in empirical datasets, Max is experienced in applying statistical learning and network analyses to -omics and medical/healthcare records datasets.
Max is currently employed as a Senior Data Scientist by the Registry of Older South Australians (ROSA), focusing on the analysis of large complex empirical datasets possessed by ROSA and the partners.
University of Canterbury, New Zealand
Blair Robertson is a Senior Lecturer at the University of Canterbury, New Zealand. He obtained his PhD in mathematics at the University of Canterbury in 2011. Before taking his current position, he was an Assistant Professor at the University of Wyoming, United States. Blair was awarded the Worsley Early Career Research Award by the New Zealand Statistical Association in 2015 for outstanding research from a statistician in the early stages of their career. His recent research has concentrated on spatially balanced sampling designs, classification trees and random search optimization.
University of Missouri, USA
Christopher K. Wikle is Curators’ Distinguished Professor and Chair of Statistics at the University of Missouri (MU), with additional appointments in Soil, Environmental and Atmospheric Sciences and the Truman School of Public Affairs. He received a PhD co-major in Statistics and Atmospheric Science in 1996 from Iowa State University. He was research fellow at the National Center for Atmospheric Research from 1996-1998, after which he joined the MU Department of Statistics. His research interests are in spatio-temporal statistics applied to environmental, ecological, geophysical, agricultural and federal survey applications, with particular interest in dynamics. His work has been concerned with formulating computationally efficient deep hierarchical Bayesian models motivated by scientific principles, with more recent work at the interface of deep neural models in machine learning. Awards include elected Fellow of the American Statistical Association (ASA), elected Fellow of the International Statistical Institute (ISI), Distinguished Alumni Award from the College of Liberal Arts and Sciences at Iowa State University, ASA Environmental (ENVR) Section Distinguished Achievement Award, co-awardee 2017 ASA Statistical Partnership Among Academe, Industry, and Government (SPAIG) Award, the MU Chancellor’s Award for Outstanding Research and Creative Activity in the Physical and Mathematical Sciences, the Outstanding Graduate Faculty Award, and Outstanding Undergraduate Research Mentor Award. His book Statistics for Spatio-Temporal Data (co-authored with Noel Cressie) was the 2011 PROSE Award winner for excellence in the Mathematics Category by the Association of American Publishers and the 2013 DeGroot Prize winner from the International Society for Bayesian Analysis. His latest book, Spatio-Temporal Statistics with R, with Andrew Zammit-Mangion and Noel Cressie, was published in 2019 and is free to download at spacetimewithR.org. He is Associate Editor for several journals and is one of six inaugural members of the Statistics Board of Reviewing Editors for Science.