Unravelling The Mysteries Of Giant Star-forming Clumps Using Deep Learning

I have chosen the Open University because of the strong focus on Astronomy of the BSc (Honours) Physics
degree. Inspired by the last decades full of new discoveries on the evolution of the Universe, I wanted to get a
better understanding on the formation of galaxies and modern cosmology. And especially as reports and
publications of the first image taken from a black hole by the Event Horizon Telescope have mentioned the huge
amount of data recorded and processed, I was seeing an opportunity to combine my professional skills in big
data analysis and machine learning with astronomy. I genuinely believe that big data analytics will have a lasting
impact on current and future astrophysical research.
Using distributed systems, on-premise and cloud-based, for data storage, processing and analysis has enabled me
to develop large scale machine learning models for decision support and product development during my
industry career. Over the years I have applied various supervised and unsupervised learning models for
regression, classification and clustering, mostly using Python frameworks like scikit-learn and Keras/Tensorflow
for statistical and deep learning, or PySpark for data pipelines and data analysis at scale.
With my background in big data analysis I hope I can make a meaningful contribution in leveraging deep
learning to analyse big astrophysical datasets