This paper outlines the early history of optimization technology for the design of microwave
circuits—a personal journey filled with aspirations, academic contributions, and commercial …

In this article, a probabilistic machine learning framework based on Gaussian process
regression (GPR) and principal component analysis (PCA) is proposed for the uncertainty …

This article proposes an advanced cognition-driven electromagnetic (EM) optimization
incorporating transfer function-based feature surrogate for EM optimization of microwave …

We present, in this article, an up-to-date general and brief scan of the main research
activities in RF and microwaves in Latin America. First, we geographically identify the main …

As microprocessor design scales to the 10-nm technology and beyond, traditional pre-and
post-silicon validation techniques are unsuitable to get a full system functional coverage …

As microprocessor architectures continue to increase computing performance under low-
energy consumption, the combination of signal integrity, electromagnetic interference, and …

For solving multiobjective electromagnetic (EM) problems, heuristic algorithms and
surrogate-assisted models are widely utilized. However, most of the existing optimization …

This article introduces a comprehensive approach for designing and analyzing signal
integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips …

Data-driven models belong to the most popular types of surrogates around. Their
fundamental advantages include versatility, low evaluation cost, easy handling, and a large …

As microprocessor design scales to nanometric technology, traditional post-silicon validation
techniques are inappropriate to get a full system functional coverage. Physical complexity …