Machine Learning Techniques
Daniel Murnane
Postdoctoral fellow, Niels Bohr Institute
Affiliate researcher, Berkeley National Laboratory
Daniel Murnane is a DDSA postdoctoral fellow at Niels Bohr Institute and an affiliate researcher at Berkeley National Laboratory. He works at the intersection of artificial intelligence and particle physics in his DDSA-funded project building language models for physics.
As Machine Learning Convener for the ATLAS experiment at CERN, he is responsible for aligning dozens of machine learning projects run by the 3000 scientists of the ATLAS collaboration. He has run machine learning tutorials in Frankfurt, Berkeley and CERN, and is a teacher for the University of Copenhagen's Applied Machine Learning course.
His work has given him expertise in most areas of AI, and he leads the effort to build an AI assistant for the ATLAS collaboration, called "ChATLAS".
Daniel is also the course director for Copenhagen Summer University's course "Machine Learning Techniques". You can read more about the course here: Machine Learning Techniques for Advanced Data.