  We propose using machine learning models for the direct synthesis of on-chip
electromagnetic (EM) passive structures to enable rapid or even automated
designs and optimizations of RF/mm-Wave circuits. As a proof of concept, we
demonstrate the direct synthesis of a 1:1 transformer on a 45nm SOI process
using our proposed neural network model. Using pre-existing transformer
s-parameter files and their geometric design training samples, the model
predicts target geometric designs.
