R&D Physicist with 10+ years of experience in developing soft and condensed matter technologies, specialising in multiscale modelling, rheology, granular materials, and polymers. Currently, as a lead Scientist, I am developing computational and experimental methods to predict structure-property relationships and design sustainable products. Highly skilled in data science (machine learning, python, PyTorch, git), modelling (molecular dynamics, DEM, ICME, and LIGGGHTS,), and experimental techniques (rheometers: MCR, MARS, CaBER, microscopes: AFM, SEM, Optical Tweezers, Confocal.In my spare time, I have been expanding my doctoral work by developing theoretical models of complex materials at various length scales to understand path-dependent properties and self-organized criticality. I'm particularly intrigued by the governing dynamics of complex systems, economic bubbles, crises, and natural computation.Collaborating beyond my doctoral work, I consistently contribute to publications alongside accomplished chemists, biologists, and physicists, promoting ways to reduce the CO2 footprint and advance sustainable technologies.