Machine Learning (ML) and Digital Twins (DT) are at the heart of today’s different industries, ranging from advanced manufacturing to biomedical systems to resilient ecosystems, civil infrastructures, smart cities, and healthcare. They have become indispensable for solving complex problems in science, engineering, and technology development. The purpose of the MMLDT-CSET 2021 conference is to facilitate the transition of ML and DT from fundamental research to mainstream fields and technologies through advanced data science, mechanistic methods, and computational technologies. This 3-day conference features technical tracks of emerging ML-DT fields and applications, special public lectures, short courses, and demonstrations. The conference will be held in a hybrid format, featuring both on-site and virtual sessions.

The goal of this MMLDT-CSET Conference is to bring together the diverse communities that are interested in learning, developing, and applying mechanistic machine learning and digital twins via computational science and engineering tools to a broad range of engineering and scientific problems, and to promote collaborations between engineers, data and computer scientists, and mathematicians from federal agencies, academia, and industry in this field.