Teaching
Machine Learning and the Physical Sciences
Spring Quarter, CME 215 (graduate level)
This course provides a survey of the rapidly growing field of machine learning in the physical sciences. It covers various areas such as inverse problems, emulating physical processes, model discovery given data, and solution discovery given equations. It both introduces the background knowledge required to implement physics-informed deep learning and provides practical in-class coding exercises. Students have the opportunity to apply this emerging methodology to their own research interests across all fields of the physical sciences, including geophysics, climate, fluids, or other systems where the same technique applies. Students develop individual projects throughout the semester.
Deep Learning in Geophysical Fluid Dynamics
Fall Semester, AOS 551 (graduate level)
This course provides a survey of the rapidly growing field of physics-informed deep learning, which integrates known physics principles with neural networks to predict the behavior of a physical system. It both introduces the background knowledge required to implement physics-informed deep learning and provides practical in-class coding exercises. Students gain experience applying this emerging method to their own research interests, including topics in geophysical fluid dynamics (atmospheric, oceanic or ice dynamics) or other nonlinear systems where the same technique applies. Students develop individual projects throughout the semester.
The Physics of Glaciers
Spring Semester, GEO 376 / ENV 375 / CEE 379 / MAE 376 / GEO 576 / AOS 579 (undergraduate level)
Glaciers and ice sheets are important elements of Earth's global climate system. This course introduces undergraduate and graduate students to the history of ice on Earth, contemporary glaciology, and the interactions between climate, glaciers, landforms, and sea level. Drawing from basic physical concepts, lab experiments, numerical modeling, and geological observations, we tackle important physical processes in glaciology, and equip students with data analysis and modeling skills. Students will gain an appreciation for the importance of ice sheets for the global climate system, and the large gaps that remain in our understanding.
Notes I put together for the topic of Ice-Sheet Dynamics