Joanne De Faveri

Dr Joanne De Faveri is a Senior Research Fellow in Statistics with QAAFI at The University of Queensland. Dr De Faveri’s research is based on developing new improved statistical and hybrid (integrated statistical / machine learning) methods to deliver significant genetic gains for plant breeding and pre-breeding programs. Her primary interests lie in spatio-temporal modelling of longitudinal data and the integration of high throughput phenotyping (HTP) (from sensors, hyperspectral, aerial images), genomic and environmental information for improved variety predictions.

Prior to joining UQ Dr De Faveri worked with CSIRO as part of SAGI-North, the Statistics for the Australian Grains Industry project, where she researched and applied statistical methods to grains research projects, in particular focussing on methods for High Throughput Phenomics. She also has over 20 years’ experience as a Biometrician with the Department of Agriculture & Fisheries (DAF), researching and applying statistical methods and training staff across a wide range of agricultural research projects in field crops, horticulture, beef, dairy, fisheries, aquaculture, and in particular, horticulture breeding programs.

Dr De Faveri has been invited to speak at National and International conferences on statistical methods for incorporating HTP data in variety trials and has developed national and international collaborations with colleagues at CSIRO, University of Queensland, University of Adelaide, Dept Agriculture & Fisheries, Wageningen University and CIMMYT.