Directly manipulating the atomic structure to achieve a specific property is long pursuit in field of materials. However, hindered by disordered, non-prototypical glass and complex interplay between property, such inverse design dauntingly hard for glasses. Here, combining two cutting-edge techniques, graph neural networks swap Monte Carlo, we develop data-driven, property-oriented route that m...