Practical Data Science: Data, models, and tall tales

Monday 30^th November 9 – 10am AEDT

Paul is a senior lecturer in the School of Mathematical Sciences and an Associate Investigator in the Centre for Data Science (CDS) and ARC Centre of Excellence in Mathematical and Statistical frontiers (ACEMS). He is passionate about developing and applying Bayesian and machine learning methods to tackle complex, real-world problems.

Paul leads a number of collaborative projects between data science researchers, applied researchers and industry practitioners, especially in ecology, and sports and physiology. His passion for collaboration has been recognised with two Vice Chancellor’s awards, for industry engagement and student mentorship on engaged research. Key, methodological interest areas for Paul include Bayesian statistics, non-homogeneous state space models, Dynamic Bayesian Networks and machine learning.