machine learning; optimization; uncertainty quantification; predictive modeling

Jessica  Zhang, Alireza Tabarraei, Kathryn Maupin, and myself are organizing a mini-symposium on “Data-Enabled Predictive Modeling, Machine Learning, and Uncertainty Quantification in Computational Mechanics,” in the ASME IMECE 2023 (October 29 – November 2, 2023). The symposium solicits abstracts on novel scientific machine learning (SciML) and uncertainty quantification (UQ) methods a wide range of applications across science, engineering, and medicine.