Humans rely increasingly on sensors to address grand challenges and to improve quality of
life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are …

Despite great progress in simulating multiphysics problems using the numerical
discretization of partial differential equations (PDEs), one still cannot seamlessly incorporate …

Neural networks (NNs) are currently changing the computational paradigm on how to
combine data with mathematical laws in physics and engineering in a profound way …

For more than 100 years, chemical, physical, and material scientists have proposed
competing constitutive models to best characterize the behavior of natural and man-made …

Providing therapies tailored to each patient is the vision of precision medicine, enabled by
the increasing ability to capture extensive data about individual patients. In this position …

For the first time in history, on March 17, 2020, the European Union closed all its external
borders in an attempt to contain the spreading of the coronavirus 2019, COVID-19 …

The recent development of machine learning (ML) and Deep Learning (DL) increases the
opportunities in all the sectors. ML is a significant tool that can be applied across many …

There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …

Multiscale simulation and homogenization of materials have become the major
computational technology as well as engineering tools in material modeling and material …