Materials that Learn by Themselves: Fundamental Concepts for New Materials - Lecture 1

Explore the groundbreaking concepts of self-learning materials in this lecture by Andrea J Liu, part of the INFOSYS-ICTS Chandrasekhar Lectures series. Delve into how artificial neural network approaches can be applied to solve inverse design problems in soft matter, with a focus on designing mechanical and flow networks inspired by biological functions. Discover the innovative concept of bottom-up learning, which allows physical systems to learn autonomously, contrasting with the traditional top-down approach of artificial neural networks. Gain insights from Liu, a renowned theoretical soft and living matter physicist, as she presents cutting-edge research in the field of materials science and physics. This lecture is the first in a three-part series on "How Materials Can Learn by Themselves," offering a comprehensive introduction to this fascinating area of study.