Delves into the intersection of physics and data in machine learning models, covering topics like atomic cluster expansion force fields and unsupervised learning.
Discusses advanced Spark optimization techniques for managing big data efficiently, focusing on parallelization, shuffle operations, and memory management.
Explores the societal impact of science, advocating against limiting it within boundaries, and introduces 'experimental history' as a multidisciplinary approach to studying science.
Delves into EPFL's Climate & Sustainability Action Week, a collaborative 5-day program focusing on methods, outcomes, emotional expression, and team work.
