SPE WORKSHOP: Artificial Intelligence and Machine Learning in Polymer Informatics

Online

This workshop introduces participants to the emerging field of polymer informatics with a focus on machine learning techniques. Polymer informatics utilizes computational and data-driven approaches to understand and predict polymer properties and behaviors, which is essential for materials innovation. The course will cover foundational concepts in polymer science and machine learning, emphasizing the integration of these disciplines. Participants will learn how to apply various machine learning models, including regression, classification, and neural networks, to solve real-world problems in polymer science and engineering. The course will address data collection, feature selection, model training, and evaluation, specifically tailored to the unique challenges of polymer datasets. Hands-on sessions will guide attendees through the process of building and deploying models using open-source tools and libraries. The course aims to equip researchers, engineers, and data scientists with the skills needed to leverage machine learning in the development of new polymers or plastics and the optimization of existing ones. By the end of the course, participants will have a solid understanding of how machine learning can drive innovation in polymer science and plastic engineering, contributing to advancements in areas such as sustainable materials, biomedical devices, compounding, additives and high-performance polymers.