Georgia Channing, Hugging Face, "AI for Scientific Discovery is a Social Problem"

The Toronto Data Workshop brings together academia and industry to share data science and AI best practice. We are broadly interested, but especially in the code- and data-centric aspects of a project that are often glossed over. We meet weekly for an hour and most talks are recorded.

Everyone is welcome. The meeting will be held online via Zoom.

BIO: Georgia Channing is the ML for Science Lead at Hugging Face and a DPhil candidate at the University of Oxford. Her academic background is in machine learning, and her research has spanned neural architecture search, protein classification, deepfake audio detection, and hyperspectral imaging. She holds an undergraduate degree from the University of Tennessee and a Masters degree from the University of Oxford. She works now on building tools and methods to advance scientific achievement.