The main goal of the project is the team to perform theoretical and experimental research activities related to systematic analysis and scientific knowledge development about the benefits of statistics and machine learning for

(1) studying, predicting and better understanding the behavior of electronic circuits,

(2) reducing or eliminating the uncertainty and inaccuracy of measurement methods in electronics,

(3) describing, predicting and analyzing defects, errors and faults in electronic circuits,

(4) optimizing a dynamic manufacturing process and its parameters related to efficiency and quality.

Existing and new forecasting and analytical models, methodologies and algorithms will be improved and developed through the means of statistics and machine learning to support decision-making in multi-criteria and multi-factor tasks in the fields of design and analysis, testing and measurement, production of electronic circuits and devices, based on consideration of contemporary theories, research achievements and world best practices.