Keynote speakers
Hans-Peter Piepho—University of Hohenheim, DE
Hans-Peter Piepho was appointed Professor of Biostatistics at the University of Hohenheim, Stuttgart, Germany in 2001. He has been working as an applied statistician in agricultural research for more than 30 years. His main interests are related to statistical procedures as needed in plant genetics, plant breeding and cultivar testing. Recent interests include envirotype- and marker-enabled breeding, spatial methods for field trials and experimental design for various applications including two-phase experiments and multi-environment trials. Further areas of interest include network meta-analysis and measure of goodness of fit for generalized linear mixed models.
Dr. Matt Edwards—University of Auckland, NZ
Matt is a Lecturer in Statistics at the University of Auckland. His current research interests are in Bayesian nonparametric free-knot spline curve fitting and generative deep learning for gravitational wave astronomy.
Before starting his role as a lecturer, he did a two year postdoc at the University of Edinburgh with Jonathan Gair, working on data analysis strategies for the future space-based gravitational wave observatory, Laser Interferometer Space Antenna (LISA).
Dr. Nokuthaba Sibanda—Victoria University of Wellington, NZ
Nokuthaba is a Senior Lecturer in Statistics and Associate Dean - Postgraduate Research for the Faculty of Engineering at Victoria University Wellington. She worked as a Biostatistician for UK Transplant for 6 years before going down the academic route. Her first academic role was a joint appointment as a Research Fellow for the London School of Hygiene & Tropical Medicine and the Royal College of Surgeons. She subsequently moved to New Zealand in 2007 to join Victoria University, first as a Statistical Consultant, and subsequently as a Lecturer. Her research interest is in Applied Statistics with a focus on biostatistics and fisheries modelling. Specific areas of research interest include modelling disease progression and species distribution modelling in fisheries.