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Emmanuel Ngonga


MSc Agricultural Data Science

University of York

Emmanuel 2.jpeg

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

I was born in 1992 in Mandevu compound, Lusaka (Zambia). After excelling in science and mathematics at junior school I was admitted to Hillcrest National Technical High School. When I finished I got accepted into the School of Natural Sciences at the University of Zambia (UNZA) where I majored in Physics. I took particular interest in Nuclear Physics, Solar Energy Physics, Quantum Mechanics and Computational Physics, because of their immediate applicability to the many challenges Zambia and the rest of the world are facing. After completing my studies at UNZA, I got introduced to Astronomy and the ambitious program of the Square Kilometre Array with its big data challenges, so I went on to do Basic Training in Astronomy and High-Performance Computing at the Hartebeestoek Radio Astronomy Observatory in Johannesburg South Africa. This training opened my mind to the endless possibilities that Data Science offers to the various challenges of the 21st Century. So I attended a number of hackathons in Cape Town with DARA Big Data and SARAO to hone my programming skills.


Please tell us about your MSc studies and the direction of your research.

My MSc studies involved researching ways to improve the pace of soybean breeding in Zambia, by employing multispectral satellite imagery to counter the fast-changing climate conditions. I used imagery from PlanetScope, Sentinel-2 and Landsat-8 satellites along with machine learning techniques for data augmentation. This created a virtual constellation that tracked the chlorophyll levels of the soybean fields in Lusaka and Chongwe districts in Zambia, and allowed me to come up with a way of predicting the maximum potential yield and maturity period of each variety I was studying. I intend to add these techniques into an app that tracks not just the chlorophyll levels of soybean, but other crops such as maize and wheat for commercial farmers throughout the entire continent of Africa. 


What are you currently doing now that you have finished your studies, and what are your plans?

I am currently working as a part-time tutor of Computational Physics at the University of Zambia, as I await graduation from the University of York. I am also actively looking for PhD studentships in the field of Artificial Intelligence (AI). 















Emmanuel (in the blue and gold shirt) tutoring students at the 2019 Big Data Africa School in Cape Town


What started your interest in agriculture and data science?

Alan Kay once said, ‘The best way to predict the future is to invent it’. Coming from a developing country I realised that Zambia's economic emancipation can only be achieved by improving its agricultural sector. On the other hand, data science and artificial intelligence are proving to be the best tools for solving complex challenges in a world faced by nuclear threats, ecological collapse and technological disruptions.


What would your dream job be, and where?

My dream is to build an entrepreneurial venture that helps to solve complex problems that humanity is facing in areas of energy production and delivery, agriculture and space travel.


What accomplishment are you most proud of so far?

The accomplishment I am most proud of right now is the skill that I have developed to start a project knowing almost nothing about it, but then becoming very prolific at solving it over the course of relentless consistent and sustained hard work.


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

Africa's population is rising exponentially while it’s climate is changing and it is facing significant technological disruption. This will present the continent with complex challenges that only those with skills in machine learning and data science will be well placed to take on. The advent of the Square Kilometre Array, 5G internet and the Starlink communication satellite system under Space X will usher in an age that will see an explosion in data science-related professions.


What did you enjoy most about the UK while you were studying here?

I enjoyed the co-operative environment in the Centre for Novel Agricultural Products (CNAP) lab at the University of York; my lab-mates made me feel at home. I also enjoyed the general friendliness of the people of York.

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