Could you tell us a bit about your background, prior to coming to the UK? 

Before coming to the UK, I worked for Telecom Namibia in Windhoek as a business intelligence (BI) analyst and then briefly as a Lecturer at the Namibia University of Science & Technology (NUST). Additionally, I was a co-lead of a Facebook group called Developer’s Circles and also a Google Developer’s Group (GDG). These groups were responsible for organising technology-oriented talks, hackathons, tech seminars and programming training to encourage knowledge sharing and networking among the developer community in Windhoek.

Please tell us more about your PhD and your research.

I am pursuing a PhD in cancer science, focusing on adaptive radiotherapy in lung cancer. As part of my PhD I am investigating image-based data mining methods to analyse how lung tumours change during treatment. The aim is to distinguish elastic and inelastic tumour changes. This information can be used to personalise treatment through the adaptation of radiotherapy. Personalised treatment will enable the delivery of better-targeted radiotherapy and reduce toxicity to surrounding tissue.

What are your plans for when you finish your PhD? 

Upon the completion of my PhD I would like to pursue an industry career, either in data science or as a developer advocate. Also, I would like to champion the introduction of compulsory coding in all Namibian schools to prepare the youth for the Fourth Industrial Revolution (4IR).

​

​

​

​

​

​

​

​

​

​

​

​

​

What started your interest in health and data science? 

My interest in data science started while working as a BI analyst at Telecom Namibia where I was responsible for developing queries (SQL/PL SQL) and tools that gather data about the performance of various company products and present this information to the users. Though I was mainly working with text and numerical data, it was during my time at Telecom Namibia that I realised the power of data science and machine learning and how they can be applied to solve complex problems. During my Masters studies I worked on an open data project. My curiosity then led me to study data science in health, an area I had little knowledge in previously although I had a keen interest to learn and to understand medical images.

What would your dream job be, and where?

I have always been passionate about working with data or developers. Hence, I would like to work as a data scientist or program manager for one of the big tech companies, i.e. Google Health, Facebook, Twitter or Salesforce.

​

What accomplishment are you most proud of so far?

Being selected as a Mandela Washington Fellow (2017), which is a flagship program of the U.S. Government’s Young African Leaders Initiative (YALI). I had an amazing 7 week experience, networking and learning from some of the best companies in the Bay Area (San Francisco).

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

In today’s digital era, I believe coding is the new literacy. Therefore every student should be taught to code; coding teaches logical reasoning, problem-solving and to an extent how artificial intelligence (AI) works. Moreover, unless students understand what is happening behind the fancy AI models, they will not be able to fully participate in the conversations on the Fourth Industrial Revolution. In Africa, AI skills are important as they will enable African youth to leverage on data and digital technologies to build models and solutions that solve the problems that face their own continent, i.e. financial inclusion, quality education and affordable quality healthcare.

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

I have enjoyed the diversity in the UK, food and travelling the breath-taking countryside. As a football fan, it was always my dream to watch live Premier and Champion’s League matches. Since I’ve been in the UK I have been able to watch many live football games.

​

Lameck (on the left) guiding students at the University of Botswana through a DARA Big Data hackathon