MSE 298 Seminar (Zoom): AI-driven Synthesis and Characterization of Quantum Materials

Zoom meeting ID 982 8379 4389, passcode 380564

Abstract: Machine learning methods have shown tremendous success in materials science, especially in designing force fields for materials simulations, predicting material properties from their atomic structure, and building models to create atomic structure for materials that exhibit a set of desired properties. In this presentation, I will describe the application of machine learning to computational synthesis, design and characterization of quantum materials architectures.

Bio: Rajiv Kalia is a professor of physics and astronomy in the USC Dornsife College of Letters, Arts, and Sciences and a professor of materials science, chemical engineering and computer science in the USC Viterbi School of Engineering. His multidisciplinary research concentrates on modeling, simulations and application of machine learning to material synthesis and characterization.