Antoinette Tordesillas

Professor Antoinette Tordesillas is a Professor of Applied Mathematics in the School of Mathematics and Statistics, Faculty of Science, at the University of Melbourne. Her research intersects mathematics, engineering, physics, and geophysics, focusing on the micromechanics of granular materials, complex networks, force chains, shear banding, and dynamical systems. She develops advanced data analytics tools, including the Spatiotemporal Slope Stability Analytics for Failure Estimate (SSAFE) model, which predicts landslide boundaries up to two weeks in advance by analyzing spatiotemporal patterns in satellite imagery and seismic data. This work supports disaster risk reduction for vulnerable communities and has been applied to forecast climate-induced extreme weather events and slope failures in regions like Nepal. Tordesillas heads the Micromechanics of Granular Media Group and collaborates internationally with organizations such as NASA, the US Army Research Office, and the Hong Kong Research Grants Council on projects involving extraterrestrial regolith simulation and seismic prediction.

Antoinette Tordesillas holds a PhD and joined the University of Melbourne's Department of Mathematics and Statistics in 1996, taking a joint appointment in geomechanics in 2013 and being promoted to full professor in 2016. In 2000, she received the J.H. Michell Medal from the Australian and New Zealand Industrial and Applied Mathematics Society, recognizing her as an outstanding early-career researcher in applied mathematics. Key publications include 'Force chain buckling, unjamming transitions and shear banding in dense granular assemblies' (Philosophical Magazine, 2007), 'Force cycles and force chains' (Physical Review E, 2010), 'Revisiting localized deformation in sand with complex systems' (Proceedings of the Royal Society A, 2013), 'Minimum cut and shear bands' (AIP Conference Proceedings, 2013), and 'Preferential flow pathways in a deforming granular material' (Scientific Reports, 2019). Her contributions have advanced predictive modeling of failure in heterogeneous media, influencing fields from geohazards to materials science.

Professional Email: atordesi@unimelb.edu.au