| Session 1 | Digital epidemiology |
| Juha Karvanen, University of Jyvaskyla | External information helps to reduce selection bias in health examination surveys |
| Krista Lagus, Aalto University | To be announced |
| Ingemar J. Cox, University of Copenhagen | Inferring health information from non-health sources |
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| Session 2 | Applied probability models in biosciences |
| Broňa Brejová, Comenius University | Inference criteria for hidden Markov models in biological sequence analysis |
| Stephané Robin, INRA | Detection of adaptive shifts on phylogenies using shifted stochastic processes on a tree |
| Mae Woods, University College London | Mathematical modelling and Bayesian inference reveals new insights into structural variation of the human genome |
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| Session 3 | Functional data analysis |
| R. Todd Ogden, Columbia University | Functional Data modeling of dynamic PET data |
| Simone Vantini, Politecnico di Milano | Advances in local inference for functional data with application to tongue profile analysis |
| Bo Markussen, University of Copenhagen | Markov Component Analysis and Functional Regression |
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| Session 4 | Statistics in climate science |
| Gudrun Brattström, Stockholm University | Climate time series: signal, noise and additivity |
| Johan Lindström, Lund University | Reconstructing past landscapes - space-time modelling of compositional data with zero counts |
| James Sweeney, University College Dublin | Adressing the statistical challenges of estimating past climate from pollen sources |
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| Session 5 | Longitudinal and time to event data |
| Cécile Proust-Lima, Université de Bordeaux | Joint modelling of multiple latent processes and a clinical endpoint: application in Alzheimer’s disease |
| Kjetil Røysland, University of Oslo | Causal validity of marginal structural models for event history data and causal local independence graphs |
| Niels Keiding, University of Copenhagen | Survival analysis around a cross-section and unobserved heterogeneity |