Using machine learning to tackle complex inverse problems in semiconductor analysis (Prof. Toshio Kamiya, Assis. Prof. Keisuke Ide)

A tandem neural network capable of inferring key physical parameters of semiconductor materials from simple transistor measurements has been developed, as reported by researchers from Institute of Science Tokyo. While conventional approaches for this type of analysis require hours or even days, the proposed system produces results in under one millisecond with near-perfect accuracy.