Professional Summary
Avi works on Bayesian inference for gravitational-wave astrophysics. He is a postdoctoral research fellow at the University of Auckland, working with Prof. Renate Meyer. His research spans LVK parameter estimation and Bayesian noise modeling for LISA.
Education
PhD Astrophysics
Monash University
BA Computer Science & Physics
The College of Wooster
Interests
Gravitational-wave astrophysics
Bayesian inference
Creative coding & game jams
Selected Publications
(2025).
Analysis of GWTC-3 with fully precessing numerical relativity surrogate models.
Physical Review D.
(2025).
Variational inference for correlated gravitational wave detector network noise.
Physical Review D.
(2025).
Bayesian power spectral density estimation for LISA noise based on P-splines with a parametric boost.
arXiv.
(2023).
Asimov: A framework for coordinating parameter estimation workflows.
Journal of Open Source Software.
Games & Experiments
In my spare time, I work on game development and human–machine learning projects. This includes reinforcement learning in games and unconventional control schemes (e.g. webcam-based tracking).
Contact
Email: avi.vajpeyi@auckland.ac.nz
Phone: +64 22 543 1418
Office: Building 303, Room 305, University of Auckland, New Zealand
Hours: Weekdays 08:30-16:30 NZT
GitHub · LIGO GitLab · Itch.io