Speaker : Dr. Daniele Huppenkothen (University of Amsterdam)
Date : 3rd December, 2024
Title : Hacking the Universe: Leveraging Data Science
in High-Energy Astrophysics and Beyond
Abstract : In data science, the concept of 'hacking' involves ingeniously
repurposing solutions from diverse fields to tackle new and
complex challenges. My group uses this approach to address fundamental
astrophysical questions by drawing on methods and tools originally
built for disparate problems in industry or other academic fields.
This talk focuses into two such questions, spotlighting the breadth
of research areas in astrophysics where data science proves invaluable.
Firstly, I will showcase how we use data-driven discovery to unravel
the physics behind magnetars — strongly magnetized neutron stars —
responsible for triggering and emitting X-ray and (sometimes)
radio bursts. In the spirit of hacking, I will also highlight how we
apply some of the same methods to other astronomical fields, from
asteroids to accreting supermassive black holes.
I will then go on to discuss how my group uses machine learning models
to accelerate astrophysical inference in black hole X-ray binaries
by several orders of magnitude, and how they enable us to ask new kinds
of research questions with existing data sets. Dispelling the
misconception that machine learning tools are only applicable to
datasets from large surveys, I will show how we deploy them extremely
effectively when our data and models are especially complex.
Throughout, I will emphasise the collaborative nature of interdisciplinary
research, underscoring the interconnectedness among communities,
methodologies, tools and software across domains. Fostering effective
and equitable collaborations is a key requirement for successful
interdisciplinary research, and I will highlight recent results in
leveraging hackathons for successful community building.
