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Event Series Event Series: Special Seminar Series

Leveraging Simulators for ML Inference in Particle Physics

April 25 @ 2:00 pm

Abstract: The field of research investigating machine-learning (ML) methods that can exploit a physical model of the world through simulators is rapidly growing, particularly for applications in particle physics. While these methods have shown considerable promise in phenomenological studies, they are also known to be susceptible to inaccuracies in the simulators used to train them. In this work, we design a novel analysis strategy that uses the concept of simulation-based inference for a crucial Higgs Boson measurement, where traditional methods are rendered sub-optimal due to quantum interference between Higgs and non-Higgs processes. Our work develops uncertainty quantification methods that account for the impact of inaccuracies in the simulators, uncertainties in the ML predictions themselves, and novel strategies to test the coverage of these quoted uncertainties. These new ML methods leverage the vast computational resources that have recently become available to perform scientific measurements in a way that was not feasible before. In addition, this talk briefly discusses certain ML-bias-mitigation methods developed in particle physics and their potential wider applications.
Bio: Dr. Aishik Ghosh is a postdoctoral scholar at UC Irvine and Berkeley National Lab where he develops innovative machine learning solutions for particle physics, and is part of the ATLAS collaboration. He earned his Ph.D. from University of Paris-Saclay where he developed the first deep generative models for fast calorimeter simulation in the ATLAS experiment. Since then he has worked on several topics at the intersection of ML and uncertainty quantification and uncertainty mitigation, including applications in astrophysics, as well as generative models for physics simulation. Recently, he has been working on reinforcement learning methods for particle physics. Dr. Ghosh has fostered interdisciplinary collaborations within academia and with industry. He has contributed to a book on Artificial Intelligence for High Energy Physics and organises ML training schools for graduate students. Dr. Ghosh consults on AI policy with international organisations like the OECD, with whom he has published writings on Trustworthy AI and AI for Science, and has given interviews to organisations like The Royal Society,


April 25
2:00 pm
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HDSI General


Aishik Ghosh


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