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Vivian Otieno


MSc Astronomy & Astrophysics

University of Leeds


Could you tell us about your background? 

I have a Bachelor of Science in Astronomy & Astrophysics from the University of Nairobi. After my BSc I was awarded a scholarship to undertake a Masters  in Space Mission Design & Management at Sapienza University. During this I got the opportunity to participate in the 1KUNS-PF mission in 2018, the first Kenyan-owned satellite to be launched into space. This was a 1-Unit Cubesat mission aimed at increasing the ability of Kenyan Universities to utilise space resources for sustainable development. I also worked on observational space debris campaigns and the attitude dynamics of near-Earth space objects (focussing on cubesats, which are smaller satellites built for space research). In addition I interned at the San Marco space station, working on satellite tracking, telemetry and communication. After this I was awarded a partial scholarship to undertake an MSc in Physics at the University of Nairobi, focusing on the orbital and attitude dynamics of cubesats.


Please tell us about your current research.

I am currently working on a project that entails using machine learning techniques to catalogue radio sources in the CORNISH South survey. I have developed a classifier in PyTorch, a Branch-Convolution Neural Network (B-CNN).


What are your plans for when you finish your Masters? 

After this programme I intend to undertake a PhD in Observational/Computational Astronomy; I am particularly interested in (exo)planetary systems, stars and galaxies. I am passionate about Space Situational Awareness, thus my keen interest in (exo)planetary systems, from which we can learn more about how we can most sustainably optimise the use of Space.














What started your interest in astronomy and data science? 

As far back as I can remember I have always been interested in astronomy, ever since I was a child. It is one of those things that you find yourself loving so much that it becomes your lifelong passion. Over the course of attending various workshops and seminars I found that I was always participating in projects using big data, sparking my interest in machine learning.


What would your dream job be, and where?

I don't have a dream job as I like experiencing different things, so whatever is in alignment with my passion would be my dream job. It wouldn't matter wherever it is particularly; as long as I'm inspired about what I'm doing that would be 'It' at that particular time for me. I feel very passionately about Astronomy and the use of Space for the bettering of humanity.

What accomplishment are you most proud of so far?

My biggest accomplishment is being 'Me' and never giving up on my dreams.

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

I wouldn't say those with machine learning skills are necessarily more advantaged than people without, each of us is unique and that's our life's  contribution. Having machine learning skills is a contribution and those who have them will bring those necessary skills to contribute to developing Africa. The world is moving into the Big Data era and machine learning is a key tool. Thus, Africa won't be left behind in contributing to global technology advancements.


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

It’s too early to conclude, but so far I really like the weather. I am looking forward to visiting Scotland. Some of my favourite artists are from the UK so I'll be attending some concerts and art shows. I like the diverse people that I've interacted with. When you focus on astronomical objects sometimes we forget that Earth is one of them; I've met people from places that I never really knew existed before and I can interact with them. I've met diverse cultures in other countries before but sometimes there can be a language barrier and I would need to depend on translating apps to communicate.

Vivian talks through her research at the Advanced Student Event held at Goonhilly Earth Station in December 2019. 

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