Our Liverpool Virtual Seminar Series on Data Intensive Science will continue on Tuesday 10th February at 15:00 GMT. The seminar will be given by Felix Yu of Harvard University who will present “Towards improving neutrino telescopes with machine learning”
Seminars in this series cover R&D outside of the data intensive science CDT’s core research areas and give an insight into cutting edge research in this area. At the end of the talk there will be a Q&A session with the speaker.
About the talk
Neutrino telescopes detect rare particle interactions originating from some of the most extreme environments in the Universe. They achieve this by instrumenting a cubic-kilometer volume of transparent medium with light sensors. Owing to their size and the prevalence of background events, these detectors produce enormous amounts of high-dimensional, highly variable data. Such characteristics pose major challenges for predicting event properties such as direction and energy, particularly with machine learning (ML) methods. In this talk, I will present an efficient point cloud transformer model designed to address these challenges. I will also discuss a self-supervised training strategy that shifts the majority of learning to real data, thereby reducing reliance on simulations and mitigating associated systematic uncertainties.
About the speaker
Felix is a 4th-year PhD student at Harvard working at the intersection of neutrino astrophysics and deep learning. His research focuses on developing novel methods and adapting cutting-edge AI techniques to neutrino physics, with the goal of accelerating fundamental scientific discovery.
How to attend
Participation is free, but you need to register to attend this and other webinars in the series. For more information and how to register please follow this link. Once registered, you will receive the Zoom connection details on the morning of the online seminar.
The seminar details
Speaker: Felix Yu (Harvard University)
Seminar title: “Towards improving neutrino telescopes with machine learning”
Date/Time: Tuesday 10th February at 15:00 GMT