I am interested in Type Ia supernovae as distance indicators, the physics of Type II supernovae (like the explosion mechanism), and on other types of transients in general (e.g., peculiar supernovae, kilonovae, tidal disruption events, etc.). My interests also lie in data science (e.g. deep learning) and coding in Python. I am an active member of ePESSTO+ where I am incharge of the data-reduction pipeline. My current work focuses on PISCOLA, a data-driven type Ia supernova fitting code and on the light curve analysis to find an alternative parameterisation to improve the precision in distance measurements.
PhD in Astronomy, 2021 (expected date)
University of Southampton
MSc in Astrophysics, 2017
Pontificia Universidad Católica de Chile
BSc in Astronomy, 2015
Universidad de Chile
Advance coding with Python (pandas, astropy, scikit-learn, etc.) including Open Source software development and JOSS referee
Experience with different statistical tools (e.g., Bayesian analysis)
Experience with different Linux distros
Machine learning for regression, outlier detection, classification, etc. Former LSSTC Data Science Fellow
Deep learning with Keras and Pytorch packages. Participation in Kaggle competitions
Spanish (native), English (fluent) and French (basic)
I love playing the drums, it is one of my hobbies. Let me know if you want to jam!