MPhil Cancer Sciences
University of Manchester
Could you tell us a bit about your background?
My background is in Applied Physics. I studied Microprocessor Technology and Instrumentation at the University of Nairobi and specialised in Industrial Electronics. After completing my undergraduate degree I worked in Fintech as an EMV developer while working on other electronics-based projects. I also co-founded Sign-IO, a company that uses technology to translate sign-language to speech. (This company was selected for inclusion at Pitch@Palace Africa 3.0, an event with royal patronage that celebrates the work of entrepreneurs and innovators. It placed second in the overall competition and won the prestigious People's Choice Award. You can read more about the event here.)
Please tell us about your MSc studies and your research.
I’m undertaking an MPhil in Cancer Sciences. My project finds features from radiographic images (radiomic features) that can predict treatment outcomes in cervical cancer patients. Since these features are numerous, I aim to apply machine learning methods to pick out those that give information pertaining to a patient’s treatment outcome. My research has potential for personalised treatment and a reduction in radiotherapy-related side effects such as toxicity.
What are your future plans?
After I finish my MPhil I hope to do a PhD to further my research in data science and applications in medical sciences.
When did your interest in data science and health sciences begin?
I found my physics and mathematics classes very enjoyable in school and I wanted to pursue medicine. When selecting which course to take in my undergraduate studies I looked for one that would allow me to apply physics to medicine. My interest in data science started with my undergraduate final year project of developing a forest monitoring system. Although my main focus for the project was designing electronics I was fascinated by the data science aspects of it; data collected from the sensors could predict the conditions in the forest and over time, this data could potentially have been used to forecast conditions that could lead to forest fires. From that point I was determined to do research that combined both data science and health sciences, which made this Masters’ project perfectly ideal for me.
What would your dream job be, and where?
My dream job is not strictly defined at the moment, but it would be in research (academic or industry) and would entail finding new or better ways to approach a problem.
What accomplishment are you most proud of so far?
I’m most proud of the research skills that I have been gaining. Every notable improvement in my research skills also makes me proud.
What advantages do you think there are for students with machine learning skills, particularly in Africa?
There are large amounts of data being generated every day, in every aspect of day-to-day life. Machine learning skills enable us to quantitatively learn from past experiences and use them to potentially predict future outcomes. For instance, collecting forest cover image data over time can help inform which areas suffer from deforestation (one of the contributors to global warming), thereby prompting action to combat deforestation and restore the forest cover. Machine learning skills are therefore paramount, as they enable us to derive data-driven solutions to the challenges that we’re facing.
What have you enjoyed most about the UK while you've been studying here?
With the easing of restrictions I’m eager to explore Manchester, and possibly visit Castle Howard and Cambridge to see the King’s College Chapel. I’d like to visit Scotland (to see the Northern Lights), Bath, London and Southampton as well.