About the speakers

 

Bianca de Stavola is Italian. She graduated at the University of Padua and obtained a PhD in Statistics at Imperial College, London, in 1985. She is currently Reader in Biostatistics at the London School of Hygiene and Tropical Medicine. Within this thriving environment,  Bianca has contributed to the development and teaching of statistical methods for long-term longitudinal (i.e. life course) studies.  Most of her applied work arises from collaborations in non-communicable disease epidemiology, and in particular in breast cancer research. Current interests are causal inference methods to deal with various sources of bias.  Bianca is Guest Researcher at the Centre for Health Equity Studies (Stockholms Universitet  and  Karolinska Institutet).

Wolfgang Huber. PhD in statistical physics at University of Freiburg, Germany. Postdocs in cheminformatics at IBM Research in San Jose, California, and in microarray data analysis at the German Cancer Research Centre in Heidelberg, Germany. Since 2004, Research Group Leader at EMBL in Cambridge, UK and Heidelberg. Wolfgang is one of the core members of the Bioconductor project, an open source, open contribution software project for genomic data analysis and modelling. He is interested in new technologies, including next generation sequencing and bio-imaging, and in computational models for understanding how variations in genotypes create variations in complex phenotypes.

Jonathan Marchini trained in Mathematics and Statistics at the University of Exeter and obtained a DPhil in Statistics from the University of Oxford in 2002, where he is now a University Lecturer in Statistical Genomics and a Senior Research Fellow at Mansfield College. He leads a research group with a focus on the development of statistical methods for the analysis of genome-wide association studies. Specific areas of research include SNP and CNV genotype calling, genotype imputation, ancestry prediction, Bayesian analysis of SNP and CNV association, multiple-phenotype analysis, gene-gene interaction analysis, meta-analysis and the analysis of data from next-generation sequencing technologies. He has been and continues to be an active member of analysis groups of the International HapMap Prroject, The Wellcome Trust Case-Control Consortium and the 1000 Genomes Project.

Ornulf Borgan's main research interest is survival and event history analysis, with a particular emphasis on methodology based on counting processes. He has published a number of papers on various topics in the field, including work on multi-state models, dynamic path analysis, and case-control methodology. A recent research interest is survival prediction from high-dimensional genomic data. Borgan is co-author of the monographs Statistical models based on counting processes (Springer, 1993) and Survival and event history analysis: a process point of view (Springer, 2008), and he has been editor of the Scandinavian Journal of Statistics (2007-2009).

Simon Tavaré is a professor in the Departments of Oncology, and Applied Mathematics and Theoretical Physics at the University of Cambridge, and a group leader in Cancer Research UK's Cambridge Research Institute. He is also a Research Professor in Biological Sciences at the University of Southern California. His current research concerns  aspects  of cancer genomics, including statistical analysis of microarray and resequencing data in the  study of SNP variation, expression, copy number aberrations, methylation and microRNAs in tumors. We also use statistical methods combined with molecular markers to infer the history of somatic cell division in tissues. This has led us  to  develop experimental methods for measuring methylation cheaply in large samples, and and to develop computational methods based on Approximate Bayesian Computation for  inference in cellular Potts models.

Els Goetghebeur is Professor of Statististics at Ghent University, Belgium. From 2004 until 2008 she spent half the year in Boston as adjunct Associate Professor in the Department of Biostatistics of the Harvard School of Public Health (US). Previous appointments include further a visiting lecturer position at Stanford University (US), and faculty positions at the London School of Hygiene and Tropical Medicine (UK), Maastricht University (NL) and the Limburgs University Center (B). Her research focuses on methods for causal inference generally (e.g. for the effect of noncompliance with assigned therapy), on survival analysis and missing data problems, the design and analysis of (sequentially) randomized trials and multiple comparisons problems (for genetic data).  She is statistical expert for EMEA (the European Medicines Evaluation Agency)  and  is PI of the recently launched consortium of the industrial research fund: `Stat-Gent CRESCENDO:  CREdible SCientific Evidence for New Discoveries and Outcomes’.