Department of Chemical and Biomolecular Engineering
University of Notre Dame
Notre Dame, IN
October 4, 2022
Science-Based Data Analytics for Molecular-to-Systems Engineering
Environmental and sustainability global challenges are “wickedly” complex. Identifying impactful solutions for these challenges often requires concerted research efforts that span molecular, material, device, systems, andinfrastructure length-scales and transcend disciplines.
In this talk, we argue predictive multi-scale mathematical models, often grounded in scientific theories, provide principled approaches to realize molecular-to-systems engineering. But the selection, training, and validation of said models in practice are often more of an art than a science, despite the recent advances (and hype?) in data science and machine learning. In this talk, we explore systematic, principled approaches to building science-based mathematical models using examples from chemical engineering.