About

I am currently pursuing an MSc in Applied Mathematics at ETH Zurich. Broadly, there are three facets to how I work and think: mathematics, statistics, and an overzealous use of Linux.

My education encompasses the standard core of modern probability, statistics, and machine learning, including measure-theoretic probability, stochastic calculus, numerics, concentration inequalities, Bayesian and frequentist inference, and contemporary ML methods.

Furthermore, I have looked into a range of more specific topics, from probabilistic concentration phenomena in tensor discrepancy, through Gaussian processes for non-stationary data, to questions of robustness and trustworthiness in specific deep learning models. This work has been mostly exploratory and project-driven, arising from theses, and small research projects.

From a systems perspective, much of my coursework and research has required working in Linux-heavy (HPC) environments for numerical computing, experimentation, and automation. Beyond that, I have been an avid Linux power user for roughly a decade, spending an unreasonable amount of time optimizing my systems, automating workflows, and generally enjoying having proper control over my machines.

This blog is a personal space where I share selected projects and occasional notes on things I have actually worked through, primarily mathematics, machine learning, Linux, and programming.