
Benjamin Thorne
Graduate Student Researcher

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About me
Machine Learning Engineer, Physicist
Education

University of Oxford
2015 - 2019Doctor of Philosophy - PhD Astrophysics
University of Oxford
2011 - 2015Master’s Degree MPhys First
Experience

University of Oxford, Department of Physics
Oct 2015 - Jun 2019Graduate Student Researcher
The University of Tokyo
Aug 2016 - Sept 2017Graduate Student ResearcherI was the inaugural Kavli IPMU - University of Oxford Fellow in astrophysics. This fellowship allows for a DPhil student in astrophysics at Oxford to spend a year or more at the IPMU, conducting their research under the supervision of a local professor. I worked with Professor Nobuhiko Katayama.My work at IPMU was mainly analytical. I derived theoretical predictions for astrophysical observables in a parity-violating cosmological model, and forecasted the constraining power of the LISA laser interferometer, and LiteBIRD satellites for such a model. Show less

Princeton University
Sept 2017 - Jul 2019Graduate Student ResearcherAt Princeton I was advised by Professor Jo Dunkley, and worked on several research projects related to analysis of astronomical datasets:• Developed widely used Python package, pysm, which simulates cosmological data. This software now underpins Galactic and extragalactic sky simulations in most cosmic microwave background experiments. • Developed Bayesian pixel-fitting Python code to be applied to multifrequency cosmic microwave background datasets, and applied it to forecast the impact of spurious signals from foreground contamination on science results from the upcoming Simons Observatory. Show less

University of California, Davis
Jul 2019 - Dec 2022Postdoctoral Scholar• Developed key software pipeline for analysis of CMB data collected with the South Pole Telescope and BICEP / Keck array. This pipeline implements MCMC sampling of a large hierarchical Bayesian model for CMB images, and makes use of hardware acceleration and advanced statistical techniques. • Developed machine learning models of non-Gaussian foreground fields. Built a variational autoencoder model of Galactic emission for use in Bayesian inverse tasks, and developed new non-Gaussian analytical models.• Co-developed v3.0 of the PySM Python package. This included targeted development for performance in HPC environments, as well as the implementation of new models supporting. Show less

Berkeley Lab
Apr 2023 - Oct 2023Machine Learning Engineer
Atomic Industries
Oct 2023 - nowSenior Machine Learning Engineer
Licenses & Certifications
- View certificate

Machine Learning Specialization
CourseraAug 2022 - View certificate

Probabilistic Deep Learning with TensorFlow 2
CourseraAug 2022 - View certificate

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
CourseraAug 2020
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