I began my PhD at the University of Cambridge, UK.
I attended and helped present the CAASTRO poster at the Australian Parliament House as part of the celebration of the ARC Centre of Excellence for All-Sky Astrophysics.
I presented an update on OzDES and my development of a new spectral classification tool using Deep Learning at the ARC Centre for All-sky Astrophysics (CAASTRO) local area meeting.
July 9 – 14:
I presented my results and upcoming paper on a spectral classification tool for the Australian Dark Energy Survey at the Astronomical Society of Australia’s Annual Scientific Meeting in Canberra.
July 6 – 8:
I attended the Harley Wood Winter School at the Kioloa Coastal Campus, ANU.
June 11 – 16:
I attended the Dark Energy Survey Collaboration Meeting at the Kavli Institute of Cosmological Physics at the University of Chicago, USA. I presented my results on a new spectral classification software and my re-analysis of the SNIa cosmological sample.
I presented work on the use of deep neural networks for supernova classification to the online “Machine Learning in Astronomy” meetings hosted by CSIRO.
March 27 – 31:
I worked with the Skymapper and Zooniverse team at the Siding Spring Observatory to search for Planet 9 in the worldwide citizen science project. I helped develop the pipeline to process the several million citizen classifications during the BBC’s Stargazing Live television series.
I began work at the Research School of Astronomy and Astrophysics, Mt Stromlo Observatory, Australian National University.
I presented my work on modelling emission line spectra with multiple Gaussian components at the Gemini South Observatory in La Serena.
I presented a tutorial on DASH for classifying supernova spectra to the OzDES collaboration.
January 22 – 26:
I attended the SOCHIAS annual conference in Marbella, Santiago, Chile. I co-presented work on “Violent star formation in galaxy interactions” with Dr. Veronica Firpo.
I gave a presentation on the use of Deep Learning for supernova and spectral classification to the Astronomy and Astroinformatics departments at the University of Chile, Santiago.
Title: DASH: Deep Learning for the Automated Spectral Classification of Supernovae”
Abstract: We have reached a new era of ‘big data’ in astronomy with surveys now recording an unprecedented number of spectra. In particular, new telescopes such as LSST will soon increase the transient catalogue by a few orders of magnitude. Moreover, the Australian sector of the Dark Energy Survey (DES) is currently in the process of spectroscopically measuring several thousands of supernovae. To meet this new demand, novel approaches that are able to automate and speed up the classification process of these spectra is essential. To this end, I have developed a software package, “DASH” that uses deep learning to classify supernova spectra. The difficulties in this classification lie in the contamination from the host galaxies, and the degeneracies with type, age, and redshift of each supernova. DASH minimises the human-time involved in supernova classification, while also limiting human-bias and error so that any spectrum can be objectively, quickly, and accurately classified. It is over 100 times faster than other classification alternatives, being able to classify hundreds of spectra within seconds to minutes. DASH has achieved this by employing a deep neural network built with Tensorflow to train a matching algorithm. It is available as an easy to use graphical interface, and as an importable python library on GitHub and PyPI with ‘pip install astrodash’.
December 15, 2016:
I graduated with Honours Class I in a Bachelor of Engineering (Electrical & Aerospace) and a Bachelor of Science (Physics) from the University of Queensland, Brisbane, Australia.
December 5, 2016:
I began work at the Gemini South Observatory in La Serena, Chile as part of the AAO’s (Australian Astronomical Observatory) Australian Government Undergraduate Summer Studentship (AGUSS).