Curriculum Vitae
Summary
Jules Perret is a research engineer in gravitational-wave astrophysics at the Astroparticle and Cosmology Laboratory (APC, CNRS, Paris). His current work focuses on the LISA space mission: building fast, differentiable likelihoods in JAX for massive black hole binary sources, with an emphasis on GPU performance and numerical accuracy. He completed his PhD at APC in 2025, where he developed DeepHMC, a Hamiltonian Monte Carlo sampler that uses a neural network to learn the geometry of the log-likelihood surface in high-dimensional parameter spaces, applied to gravitational-wave parameter estimation.
Professional Experience
Research Engineer, Gravitational-Wave Data Analysis
Laboratoire Astroparticule et Cosmologie (APC), CNRS, Paris · 2025 to present
Development of JaxMBHB, a JAX library for computing the LISA instrument response and time-domain likelihood for massive black hole binary coalescences. The focus is on fully differentiable, JIT-compiled pipelines that run efficiently on GPU, enabling gradient-based samplers and fast parameter estimation at LISA sensitivity.PhD in Gravitational-Wave Physics and Data Analysis
Laboratoire Astroparticule et Cosmologie (APC), CNRS, Paris · 2022 to 2025
Thesis on Bayesian parameter estimation for gravitational-wave sources. Developed DeepHMC, a Python/PyTorch package that uses a neural network to learn the geometry of the log-likelihood surface in high-dimensional parameter spaces and uses it to precondition a Hamiltonian Monte Carlo sampler. Applied to ground-based detector signals with a focus on the Einstein Telescope. Member of the LIGO-Virgo-Kagra (LVK) collaboration.Research Intern, Astrophysics
Lawrence Berkeley National Laboratory (LBNL), UC Berkeley, CA · summers 2020, 2021, 2022
Three successive internships focused on continuous gravitational waves from pulsars. Worked on data analysis pipelines for LIGO and Virgo data and developed parallel FFT algorithms on GPU in Python and C/C++.Software Development Intern
Université de Bourgogne, Dijon · 2020
Developed mixed reality applications for the Microsoft HoloLens platform using C#, Unity, and the MRTK framework. Used 3D Slicer to process brain tomography images.Education
PhD in Astrophysics
Université Paris Cité / APC-CNRS · 2022–2025
M.Sc. High Performance Computing and Numerical Simulation
ENS Paris-Saclay, Université Paris-Saclay · 2020–2022
B.Sc. Computer Science and Full Stack Web Development
Université de Bourgogne · 2016–2020
Preparatory Year in Physics
Université de Montréal · 2014–2016