Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling


The semiconductor industry is entering an era of unprecedented complexity, driven by advanced architectures such as Gate-All-Around (GAA) transistors, wide-bandgap materials like GaN and SiC, and heterogeneous integration strategies. Traditional physics-based modeling approaches are increasingly challenged by nonlinear effects, electro-thermal interactions, and variability across device geometr... » read more

What we know after twelve years developing and deploying test data analytics solutions


Abstract: Since 2004, Texas Instruments and Portland State University have collaborated to develop and deploy test data analytical methods for use in a variety of applications, including quality screening, burn-in minimization, high cost test replacement and/or removal, and operations monitoring. In this paper, key findings amassed during this time are summarized. Find the technical paper h... » read more