Exploring the development of machine learning for materials science, physics, and chemistry applications through conversation with researchers at the forefront of this growing interdisciplinary field. Brought to you in collaboration by the Stanford Materials Computation and Theory Group and Qian Yang's lab at the University of Connecticut.

Latest episodes of the podcast Materials and Megabytes

• Paper Interview - Learning from Failure: Predicting Electronic Structure Calculation Outcomes with Machine Learning Models
• Paper interview - Screening billions of candidates for solid lithium-ion conductors: A transfer learning approach for small data
• Turab Lookman (Season 2, Ep.4)
• Patrick Riley (Season 2, Ep. 3)
• O. Anatole von Lilienfeld (Season 2, Ep. 2)
• Gábor Csányi (Season 2, Ep. 1)
• Evan J. Reed (Season 1, Ep. 3)
• Ekin Dogus Cubuk (Season 1, Ep. 2)
• Kieron Burke (Season 1, Ep. 1)
• Introduction (Season 1, Ep. 0)