Data Scientist | Astrophysicist
Transforming massive astronomical datasets into actionable insights through advanced statistical modeling, signal processing, machine learning, and scalable data pipelines. Astrophysics PhD specializing in large-scale data analysis and scientific computing.
Expertise in data science, signal processing, machine learning, and high performance scientific computing
Data-driven solutions and research
Developed automated pipeline processing time-ordered data from the Simons Observatory, achieving 95% detection accuracy for rapid astrophysical transients using custom matched filtering and machine learning algorithms.
Stacking analysis code to measure the polarization fraction of Planck Galactic cold clumps and generate fullsky source masks in HEALPix format for CMB surveys.
A self-organised project with a comprehensive demonstration of common data engineering practices through the use of Python, Apache, SQL, and Flask. This project implements a complete ETL pipeline for stock market data.
I'm a data scientist who recently achieved a PhD in Astrophysics from The University of Melbourne, specializing in analysing large-scale datasets from astrophysical instruments. My research with the Simons Observatory has given me extensive experience in statistical modeling, signal processing, machine learning, and building production-ready data pipelines.
I'm driven by diving into messy, real-world data and turning it into clear, insightful outputs. Whether it's developing algorithms to detect rare, rapid astrophysical transient events, or building systems to run statistical analysis of large data catalogues, I thrive on solving challenging data problems.
Beyond technical skills, I'm passionate about communicating my findings to diverse audiences -- from academic presentations to public outreach events. I believe great data science should combine technical rigor with the ability to tell compelling stories from the data.
When I'm not coding or exploring the Universe: You can find me exploring the corners of world, stargazing (naturally!), or sharing the wonders of science with the next generation. I'm a big sports fan, and can't go past a good movie, TV or book as a way to wind down in the evening!
Open to data science/analysis opportunities and collaborations