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School of Electronic Engineering and Computer Science

Alumni profile - Terence Michael Egbelo (Data Science and Artificial Intelligence MSc, 2021)

Terence pictured in front of mountains and a lake on his travels

Terence studied our Data Science and Artificial Intelligence MSc after taking some time out to travel the world, and has recently started a PhD at the University of Sheffield. Terence shares what he enjoyed about studying his subject, as well as some valuable advice for future postgraduate students.

Tell us a bit about your time at Queen Mary, including any special or favourite memories:

"Our course, being a conversion MSc, was the start of a big change for my coursemates and I, each coming from a non-computer science background. So, there was a real sense of a special kind of camaraderie and willingness to learn as a team from the start.

I also had the pleasure of working on a research report to understand the evolving technology needs of wheelchair users in the communities surrounding Queen Mary, covering east and southeast London. It was a great opportunity to put my developing skills into service and be exposed to more of the diversity of lived experience in our city."

Why did you choose to study MSc Data Science and Artificial Intelligence at Queen Mary?

"During lockdown in New Zealand, I developed a real passion for programming. I was already in a process of re-orientation and resolving to build a data science skillset just felt right. About two months into intensive self-study, I knew I was serious about this and was looking for the next level, so the decision to pursue a masters came quite naturally to me. My brother had really enjoyed his MSc in Banking at Queen Mary some years prior, so it was one of the first universities I thought of, and it was good fortune that the university was piloting the conversion MSc in Data Science and Artificial Intelligence that same year."

Which modules did you most enjoy?

"I particularly enjoyed Natural Language Processing. NLP is a uniquely fun combination of linguistics and computer science. We worked on problems like detecting fake Amazon reviews and identifying soap opera characters by their script lines, but above all, the module worked well as a hands-on, in-at-the-deep-end bootcamp on data exploration, cleaning and pre-processing, right through to machine learning model development and evaluation. There were certainly highlights across other modules, like for example the thorny issues we grappled with each week in the Data Ethics module – I could be here all day listing my memories!"

Were you a member of any societies or volunteering groups during your time at Queen Mary? What did you gain from them?

"I joined many of the talks and discussions hosted by Queen Mary’s interdisciplinary Institute of Applied Data Science. The weekly lecture series is run by a group of enthusiastic PhD students, and they regularly invite top academics and industry practitioners from the world of AI and data science to speak. It is an invaluable community for students wanting to understand the landscape and keep up to date with the latest research and application trends."

"If you want a job, learn what skills will make you stand out besides your course work, and understand how the jobs you’re aiming for impact company bottom lines."


How has your master’s degree and your time at Queen Mary prepared you for your current PhD studies?

"The MSc was an intense experience where a deadline (or an exam!) was always on the horizon. So perhaps first and foremost it was a thorough exercise in self-motivation and time management. Planning out the time needed for assignments, knowing when to move on to the next bit of work and having the belief that if you get stuck you will find a solution – even if it isn’t the one you originally expected – are all abilities I know will be key in my PhD studies."

What are your career plans for the future?

"As part of my PhD, I hope to contribute to developing novel graph data mining and machine learning approaches to help reduce the cost and speed up the process of drug development.

Following my PhD, I will look to transition into a research position within industry. Modern biotechnology is a fascinating field, and the latest experimental techniques are producing massive amounts of very detailed data, which means an ever-growing need for powerful computational methods to extract the insights about human health hiding in the data. Not a bad industry for promising start-ups either!"

What advice would you give to future Data Science and AI students?

"Be sure that you’re having fun with the subject. If you can geek out and you don’t get easily frustrated when the computer isn’t doing what you expect, I’d say you’ve already got a foundation for a fruitful year. But also take some time from the start to consider what you want to do with your degree. There are definitely good job opportunities straight out of it, and there’s also the PhD route; both are very competitive.

If you want a job, learn what skills will make you stand out besides your course work, and understand how the jobs you’re aiming for impact company bottom lines, or how they contribute to policy objectives, if in the public sector. If you want to go into research, do your best to find an area you’re very interested in, then home in on as sharp a research problem as you can. And don’t forget to talk to Queen Mary academics! You never know what or who you’ll get to know."

This profile was conducted by Alumni Engagement Officer, Nicole Brownfield. If you would like to get in touch with Terence or engage him in your work, please contact



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