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David Bastien


MSc Astronomy

University of Manchester


Could you tell us about your background? 

I was born and raised on a nice island in the Indian Ocean called Mauritius. I did my bachelor’s degree in physics with a minor in astrophysics at the University of Mauritius and graduated in 2016. After my degree I worked as a research assistant in a market research company in Mauritius and after three years I became a data specialist in the same company. 


Please tell us about your MSc studies and your research.

My MSc focused on generative algorithms and deep learning methods to generate radio sources, in particular Active Galactic Nuclei (AGNs). These methods have been used for generating human likenesses (known as deepfakes) and I worked on adapting, building and testing these existing methods for radio astronomy. This work will be important for large radio telescopes like the SKA (Square Kilometre Array) as these source simulations will help with testing data pipelines (from source detection to source classification).

My work on simulating populations of radio galaxies was recently accepted and published in the Monthly Notices of the Royal Astronomical Society

What are your future plans?

Following my MSc I started a short work placement at SKAO which continued my research and directly applied it to the SKA Telescope. After researching this topic for the past 18 months I’ve realised that there is much more work to be done when it comes to applying machine learning (ML) to radio astronomy or even astronomy. I want to pursue that type of big data-oriented research and become a specialist in using machine learning in astronomy and more precisely in using generative algorithms for radio astronomy and other related fields.









When did your interest in deep learning begin? 

I first came upon the concept back in 2015 through a Joint Exchange Development Initiative (JEDI) Workshop held in Mauritius. I was in my second year of university studying physics and was really interested in astronomy and programming and wanted to focus on them. Inspired by the ML and deep learning sessions of the workshop I made a proposal to my department to do a project combining machine learning and radio astronomy, which I did in my third year. I eventually submitted my BSc thesis titled ‘Detecting bent radio galaxies to trace galaxy clusters using machine learning’, which then became one of the first ML and radio astronomy papers accepted at a conference by a Mauritian undergraduate student (you can read it here). From that point I did machine learning just for fun and did some of the online MIT courses, but my interest in machine learning grew stronger when I got a job working for a multinational market research company. There I had the chance to develop AI systems and deploy them for the company’s day-to-day operations. These two phases in my life, academic and industrial, forged my interest in machine learning (which later became deep learning) and data science overall. 


What would your dream job be, and where?

I think what you aspire to become is highly influenced by the way you grew up. My father was a carpenter and owned his own business where he trained and employed people while my mother managed all the business paperwork and accounting. As such my dream job is be to become an entrepreneur and to create jobs. As I am an aspiring data scientist, my dream job is to create one of the first consulting and research firms focused on natural language processing and machine learning in Mauritius and the neighbouring islands. 

What accomplishment are you most proud of so far?

I think one of my biggest accomplishments is coming to the UK, I have never left my island for such a long period of time before. Coming here and living on my own was a huge experience. Also surviving a global pandemic while being in the UK was really difficult but I was still able to get my Masters degree done. This I think is one of my biggest achievements so far. 

What advantages do you think there are for students with machine learning skills, particularly in Africa?

It’s really difficult for me to talk about the advantages of ML for the whole African continent, but I can talk about the advantages of these skills for students from island states like Mauritius. Firstly if we look at the macro economy of those small states one might notice that they are mostly focused on tourism, exports and a vibrant financial sector (in Mauritius at least). Therefore most students would probably choose a career in one of those sectors, however machine learning might be a strong point to focus on for these countries and their students. As an emerging industry machine learning requires only three main ‘ingredients’; data, computing power, and most importantly, algorithms. As it requires few foundations and relies mostly on human resources, machine learning provides students or entrepreneurs with an ideal business start-up and as such would be really easy to set up on island states. These skills will be more valuable to students (and to Africa generally) if they can become entrepreneurs instead of employees. 


What have you enjoyed most about the UK while you've been studying here?

One of the most amazing things is to have met so many people from different countries and cultures. I have had the chance to grow both personally and professionally for the past year or so. While living in University halls I got the chance to meet people with different professional, social and cultural backgrounds. 



David presenting his research at Goonhilly Earth Station, December 2019

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