Machine learning to accelerate data analysis in LISA
Invited talk at Enabling Future Gravitational Wave Astrophysics in the Milli-Hertz Regime, Garching, Germany
CV
Education
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
- M.S. in Jekyll, GitHub University, 2014
- B.S. in GitHub, GitHub University, 2012
Work experience
- Spring 2024: Academic Pages Collaborator
- Github University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Talks
Posterior post-processing for gravitational-wave inference
Contributed talk at European AI for Fundamental Physics Conference 2025, Cagliari, Italy
Posterior post-processing for gravitational-wave inference
Contributed talk at AIslands 2025: Bute, Rothesay, Bute, Scotland
Importance nested sampling with normalising flows
Contributed talk at European AI for Fundamental Physics Conference 2024, Amsterdam, Netherlands
Machine learning for gravitational-wave data inference
Invited talk at Challenges and future perspectives in gravitational- wave astronomy: O4 and beyond, Lorentz Center, Leiden, Netherlands
Premerger observation and characterization of supermassive black hole binaries
Contributed talk at 15th International LISA Symposium, University College Dublin, Dublin, Ireland
Importance nested sampling with normalising flows
Contributed talk at AIslands 2024: Arran, Arran, Scotland
Importance nested sampling with normalizing flows
Invited talk at 42nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, Max-Planck-Institut für Plasmaphysik, Garching, Germany
Importance nested sampling with nessai for gravitational-wave inference
Contributed talk at Glasgow G2Net Meeting 2022, Glasgow, Scotland
Importance nested sampling with nessai for gravitational-wave inference
Talk at National Astronomy Meeting 2022, University of Warwick, UK
Importance nested sampling with nessai
Contributed talk at BritGrav22, University of Glasgow (remote), UK
nessai: Improved nested sampling with normalising flows
Poster at National Astronomy Meeting 2021, University of Bath (remote), UK
Introduction to normalising flows
Invited talk at Machine Learning in Science, University of Glasgow, UK
Why is machine learning relevant to astronomers
Colloquium at Department of Physics, CSU Fullerton (remote), California, US
Incorporating machine learning into existing techniques for gravitational-wave inference: nested sampling with normalising flow
Invited talk at TianQin Research Center for Gravitational Physics, Sun Yat-sen University (remote), China
Incorporating machine learning into existing techniques for gravitational-wave inference: nested sampling with normalising flow
Invited talk at Max Planck Institute for Gravitational Physics, Albert Einstein Institute (remote), Germany
Convolutional Neural Networks for Gravitational Wave Detection
Poster at PCCP Workshop Series : Bayesian Deep Learning for Cosmology and Gravitational waves, Universite de Paris, Paris, France
Teaching
Service and leadership
- Currently signed in to 43 different slack teams