Roxanne Guenette is a Professor of Particle Physics at University of Manchester. She studies neutrinos, the least understood of all fundamental particles and a particle that could unlock the several mysteries of our Universe. Her focus is in developing new particle physics detector technologies to enable future experiments to make groundbreaking discoveries in the field of fundamental research in particle physics. She is the spokesperson of the Detector R&D Collaboration on Liquid Detectors.

She has worked with a wide range of detector technologies, with most of them having in common exquisite particle imaging capabilities. These 2D and 3D fine-grained images allow to see neutrino and particle interactions with a lot of details, to select the desired signal events and reject the unwanted background events. These images lend themselves to perfect Machine Learning applications, and there is a lot of place for improving the event reconstruction of these rare events. With the development of new detector technologies, such as pixelated readouts, the resulting intrinsic 3D images offer even more opportunities to search for unexpected phenomena and discover new physics and AI is the best bet to study the scientific potential of these new imaging devices.