Patrick Heimbach

Patrick Heimbach, a professor at the University of Texas, dives deep into the intersection of machine learning and oceanography. He discusses the challenges of simulating ocean circulation and how machine learning can significantly improve model accuracy. The importance of differentiable programming in integrating observational data with physical models is highlighted. Heimbach also explores modular oceanographic modeling and how machine learning assists in analyzing ice sheet dynamics and calving processes, showcasing a bright future for these technologies.