Simon has over a decade’s experience in developing and applying machine learning techniques to a wide range of problem areas such as behavioural prediction, robotics, demographic estimation and the sciences. He began his research into machine learning during his PhD at the University of Sydney while building a more principled framework for robots to reason about uncertainty in their surroundings. Simon has since been published in several top-tier conferences and journals as well as co-supervised PhD students in the same field.
While working for Data61 and NICTA, Simon focused on turning ideas from academia into realisable systems to solve problems being faced by industry and government. At Gradient, Simon now directs his efforts towards developing methods that ensure the AI systems we build today contribute positively to society in a manner that is both fair and transparent.