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Dexter taught foundations in machine learning to postgraduate students at the Lilongwe University of Agriculture and Natural Resources in Malawi

Some of the volunteers and students visited a local farming village and talk to the farmers about their issues and how Machine Learning can help.

Dexter Shepherd, a Doctoral student doing research on bio-inspired AI at the School of Engineering and Informatics, recently visited Malawi as a volunteer for TReND in Africa, a pioneering NGO dedicated to promoting scientific research and education in the African continent.

Founded in 2011 by Professor Thomas Baden (University of Sussex), Dr Lucia Prieto (Crick Institute) and Professor Sadiq Yusuf (Kampala International University), TReND has about 50 dedicated volunteers spread across four continents, active collaborations with approximately 20 partner universities in over ten African countries, and it has successfully implemented a range of activities, including multi-week science courses in fields such as Neuroscience, Bioinformatics, Molecular Biology, and more, taught by global experts. These initiatives, alongside invaluable infrastructural support, such as the shipping of critical lab equipment to under-resourced institutions, and the innovative development of Open Labware, have significantly bridged the gap between African scientists and their counterparts worldwide. Additionally, TReND also organises science outreach programmes with local schools which hope to inspire future scientists across the African continent.

Dexter was based at the Lilongwe University of Agriculture and Natural Resources where he and the other TReND volunteers taught foundations in machine learning to postgraduate students, equipping them with the tools to enhance their research and contribute to Malawi’s development.

The two-week training programme was comprehensive, covering theoretical concepts in the mornings and practical sessions in the afternoons, where students worked with R and Python. During the second week, students applied the models they had learned to their own datasets, aiming to improve disease classification, farming efficiency, and other relevant tasks.

While two weeks may not suffice to master machine learning, the course provided students with foundational skills that they can continue to develop. Some students were interested in real-time machine learning classification in the field.

Philip Gama, a Masters student at Lilongwe University who undertook the course said: “The AI Data Science and Machine Learning course has been so eye opening to me. It has exposed me to the immense possibilities of working with data, making predictions, and even getting insights that inform those decisions. The training experience was immense as we were trained by a selfless team that gave us hands on knowledge combined with theory in R and Python. It was my first time working with python but after the training I can confidently work with python. This training has and will open a whole world of possibilities and opportunities.”

Dexter and other volunteers also visited local farming villages to engage with farmers, gaining first-hand insight into how machine learning could be applied. This immersive experience was invaluable, providing the volunteers with a clearer understanding of the practical implications and potential impact of machine learning in real-world agricultural settings.

Lilongwe University is now planning to integrate a Machine Learning and Data Science course into their curriculum, reflecting the success and relevance of the training programme. Additionally, the collaboration with European universities, particularly the University of Sussex, has grown stronger through this initiative. Many professors involved in TReND are from Sussex, indicating a promising partnership for future endeavours.

About his experience as a volunteer, Dexter said: “I highly recommended it to any PhD student seeking to apply their skills for meaningful, real-world impact. Sometimes in academia we can get too focused on theory or on proving concepts, and we lose sight of the ultimate goal. In this trip I have witnessed first-hand the tangible benefits that these skills can bring to improve lives and potentially even to save lives. It has re-invigorated my commitment to mentor and collaborate with other universities in the global South.

I would like to express my gratitude to TReND for organising this trip, alongside so many other great projects across Africa. Professor Elizabeth Bandason, a member of faculty at Lilongwe University who hosted and supported us, and made us feel welcome so far away from our homes. Beyond this, I would also like to thank the University of Sussex School of Engineering and Informatics for funding the travel costs.”

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