Pengyuan Ding
Contact details
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 ofpredicting and designing materials with desired properties.
Research group
Integrated Computational Materials Group (ICME)
Supervisors
Qualifications
M.Sc. Mathematics and Statistics, The University of Melbourne
Gdip, Mathematics and Statistics, The University of Melbourne