We propose a framework to analyze mm-wave baluns directly from physical parameters by
adding a dimension of Machine Learning (ML) to existing electromagnetic (EM) methods …

Integrated circuit design in millimeter-wave (mm-Wave) bands is exceptionally complex and
dependent on costly electromagnetic (EM) simulations. Therefore, in the past few years, a …

A computational approach to automate mm-wave Directional Couplers can greatly improve
upon the current techniques that rely on trial-and-error. To build such an automated …

This work describes deep-learning-enabled inverse design of multi-port electromagnetic
(EM) structures co-designed with circuits that can enable the synthesis of novel high …

As fifth-generation (5G) and upcoming sixth-generation (6G) communications exhibit
tremendous demands in providing high data throughput with a relatively low latency …

This paper presents neural network and genetic algorithm based modeling and design of
millimeter wave RF front end circuits. The neuro-genetic design methodology is composed …

Interests in millimeter-wave (mm-wave) circuits are rapidly growing, partly promoted by
semiconductor technology advancements and design environment improvements. However …

In this paper, the application of regression-based supervised machine learning (ML)
methods to the modeling of integrated inductors and transformers is examined. Different ML …

In this paper, several machine learning modeling methodologies are applied to accurately
and efficiently model transformers, which are still a bottleneck in millimeter-wave circuit …

This article presents a 4: 1 wide-band balun that won the student design competition for
wide-band baluns held during the 2016 IEEE Microwave Theory and Techniques Society …