A3D3 seminar: Accelerating Discovery in Particle Physics with Anomaly Detection

Abstract: Modern machine learning and artificial intelligence are starting to fundamentally change how we analyze huge volumes of data in particle physics and adjacent scientific disciplines. These breakthroughs promise new insights into major scientific questions such as the nature of dark matter or the existence of physical phenomena beyond the Standard Model of particle physics. This talk will provide an overview of recent, exciting developments with a focus on model agnostic discovery strategies - including the use of in-situ generative models, ultra-fast outlier detection, and new experimental results.
Gregor Kasieczka joined Universität Hamburg in 2017 where he is a professor for machine learning in particle physics. His work focuses on searches for exotic new particles with the CMS experiment and on developing new techniques for simulation and data analysis in fundamental physics. He is an author of the first textbook on machine learning for physicists “Deep Learning For Physics Research”.

The A3D3 Seminar is a monthly lecture series that hosts scholars working across applied areas of artificial intelligence, such as hardware algorithm co-development, high energy physics, multi-messenger astrophysics, and neuroscience. Our presenters come from all four domain fields and include occasional external speakers beyond the A3D3 science areas, governmental agencies and industry. The seminar will be recorded and published in RUclips. To receive future event updates, subscribe here.
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