Abstract: In this talk, I will discuss recent publications from my group that attempt at learning models of the world and the effect of the actions of an agent within […]
Abstract: Machine learning tools have tremendous potential to accelerate computationally complex physics-based simulations. One example is the need to accelerate materials discovery through first-principles Density Functional Theory (DFT) calculations. This […]
Abstract: Understanding the physical processes modulating the transport of scalars, such as heat, over very rough surfaces is essential for understanding the thermal environment of cities, how wind and solar […]
Abstract: Polymers are essential to a wide range of technologies, yet designing them with targeted structural and functional properties remains a grand challenge. A major opportunity lies in applying machine […]
Abstract: To meet net-zero carbon emissions targets by mid-century, up to a ~30-fold increase in wind power capacity is required. Acceleration to this rate requires urgent improvements to efficiency and […]
Abstract: The volume fraction phi for random close packed (RCP) spheres is approximately 0.64. It is well known that higher RCP volume fractions are achieved by using collections of particles […]
This speaker event is virtual, but will be screened in PICS 534 with refreshments. Abstract: Equilibrium thermodynamics emerges from equilibrium statistical mechanics as the most likely behavior of a system […]