Three eras of my dotfiles
We tour a chezmoi-templated dotfiles setup that bootstraps a fresh machine in one command — terminal, shell, prompt, multiplexer, multi-environment templating, and the developer …
Gaussian Process Regression in 9,000 Google Sheets Cell Formulas
We implement a fully functional Gaussian Process regression pipeline — Cholesky decomposition, posterior predictions, and gradient-based hyperparameter optimization — in pure …
📄 One paper accepted to ICML 2026
Our paper "Empirical Gaussian Processes" was accepted to ICML 2026.
📄 One paper accepted to AutoML 2025
Our paper "Ax — A Platform for Adaptive Experimentation" was accepted to AutoML 2025 (ABCD Track).
💼 Joined Meta CAS Adaptive Experimentation
Started as a Research Scientist at Meta on the Adaptive Experimentation team within Central Applied Science (CAS), based in New York City.
🎓 PhD thesis completed
Submitted my PhD thesis, *Probabilistic Machine Learning in the Age of Deep Learning*, at the University of Sydney.
PhD Thesis Acknowledgements (Unabridged)
The unabridged acknowledgments from my PhD thesis.
•
1 min read
📄 One paper accepted to ICML 2023
Our paper "Spherical Inducing Features for Orthogonally-Decoupled Gaussian Processes" was accepted to ICML2023 as an Oral Presentation!
•
1 min read
Efficient Cholesky decomposition of low-rank updates
We give a short and practical guide to efficiently computing the Cholesky decomposition of matrices perturbed by low-rank updates.
📄 One paper accepted to NeurIPS 2022
Our paper "Batch Bayesian Optimisation via Density-ratio Estimation with Guarantees", led by Rafael Oliveira, was paper accepted to NeurIPS2022!
•
1 min read