This video covers the essential concepts of sequential data modeling and modeling approaches such as transformers.

Carlo Graziani is a Computational Scientist at Argonne National Laboratory. He received a Ph.D. in physics from the University of Chicago in 1993. He has worked on research problems in high-energy astrophysics, computational fluid dynamics, high-energy density physics, and plasma physics, as well as in applications of advanced statistics and machine learning to physical and biological problems. He joined Argonne in 2017.

Troy Arcomano is a postdoctoral fellow at Argonne National Lab working on machine learning applications for weather and climate in the EVS division. During his time at ANL, he was the Argonne lead for several projects including a large collaboration to create a state-of-the-art foundation model for weather prediction. Troy received his PhD at Texas A&M University where he worked on developing machine learning applications for weather forecasting and investigated how machine learning could be used to improve climate models. He'll be speaking about the AI revolution for Weather and Climate.