Py Ding

Thesis Title

Data-efficient and physics-informed inverse design of hierarchical polymer composites using machine learning and statistical optimisation

Research overview

Exploring the potential of integration of optimisation and machine learning methods into
the inverse design of multiscale polymeric materials, to accelerate the process of
predicting and designing materials with desired properties.

Supervisors

Dr Ellie Hajizadeh
Prof Michael Kirley
Dr Dominic Robe
Dr Mario Munoz Acosta

Qualifications

M.Sc. Mathematics and Statistics, The University of Melbourne
Gdip, Mathematics and Statistics, The University of Melbourne