Interdisciplinary Research and Education for a Computational Future

Explore the challenges and needs for addressing critical societal issues across science, engineering, and medicine in this 49-minute talk by Karen Willcox from the University of Texas, Austin and Santa Fe Institute. Discover the concept of "predictive data science" and its importance in high-consequence decision-making. Learn why a synergistic combination of modern data-driven approaches and classical physics-based perspectives is crucial. Examine the significance of maintaining the predictive power, interpretability, and domain knowledge associated with physics-based models while embracing machine learning and artificial intelligence. Delve into the implications and requirements for interdisciplinary education in shaping a computational future.