About
This joint seminar between the Physics Department and The Triangle Universities Nuclear Laboratory will feature Dr. Michelle Kuchera.
About the seminar:
Machine learning has become ubiquitous in data-rich applications. Fundamental physics research provides an exciting realm for machine learning research with applications ranging from experimental data acquisition through making theoretical predictions. This talk will step through machine learning theory from neural networks to Generative Adversarial Networks, highlighting applications in low through high energy nuclear physics research. Specifically, Dr. Kuchera will focus on applications that her group, ALPhA (Algorithms for Learning in Physics Applications), have completed in collaboration with the Facility for Rare Isotope Beams and the Thomas Jefferson National Accelerator Facility. She will highlight areas where nuclear physics applications can inform machine learning innovation, providing a rich environment for the advancement of both nuclear physics and machine learning research.