According to psychologist D. Kahneman (2002 Nobel prize winner in economics for the work on decision making under uncertainty) there are two modes/systems of thinking. System 1 operates automatically and quickly, like deep learning empowered by automatic differentiation. System 2 allocates attention to the effortful mental activities, like building explainable heuristics in quantitative sciences.
In this talk we illustrate how applied mathematics is harnessing system 1 achievements of modern AI to build system 2 for quantitative sciences. Specifically, we discuss design, training and validation of the system 2 for
1. Physics Informed Machine Learning of Power Systems
2. Lagrangian Large Eddy Simulations of Turbulent Flows
3. Graphical and Agent Based Models of epidemiological bursts
Bio:Dr. Michael (Misha) Chertkov is a Professor of Mathematics and Chair of the Graduate Interdisciplinary Program (GIDP) in Applied Mathematics at the University of Arizona (UArizona). Dr. Chertkov area of focus is mathematics, including statistics and data science, applied to physical, engineered and other systems and networks. He has published more than 250 papers, is a fellow of AAAS, a fellow of the American Physical Society and a senior member of IEEE.