- Why the judges said it could transform MRI in Nigeria without buying a single new machine
- First woman and first millennial individual winner
- Record 237 entries
- Award Night 9 October 2026
By Chido Nwakanma
On 8 September 2026, in a Lagos press room that has become an annual fixture for Nigeria’s most closely watched science prize, Professor Barth Nnaji announced a result the competition had withheld the year before.
After a 2025 cycle that ended with no winner — a deliberate choice to protect the prize’s standard — the Nigeria Prize for Science and Innovation (NPSI) had a name. Mary-Brenda Akoda, a Nigerian AI researcher and founder from Calabar South in Cross River State, had been selected unanimously for GenScan AI, also known as GenMRI/C-MORE: software designed to reconstruct MRI images from far less acquired data, with reported potential to cut scan times by as much as 90 per cent on existing machines.
The award, sponsored by Nigeria LNG Limited and worth US$100,000, is one of Africa’s largest science prizes and a counterpart to the Nigeria Prize for Literature. Akoda will receive it at the Grand Award Night on 9 October 2026. The 2026 result marks the twelfth winning work in the prize’s twenty-two-year history, now rebranded as The Nigeria Prize for Science and Innovation. NLNG has also recently instituted a third prize for creativity.
A historic first — After a Year of None
Akoda’s victory is historic on more than one count. She is the first woman to win the Science and Innovation Prize as an individual recipient. She is also the first millennial to do so; previous winners in the prize’s run had often entered as teams. She was chosen from a record 237 entries — the highest number since the prize began — under a theme retained from the empty 2025 cycle: “Innovations in Artificial Intelligence, ICT and Digital Technologies for Development.”
That retention was not accidental. Nnaji, chairman of the NPSI Advisory Board, told the gathering that keeping the same theme after a “no winner” year challenged Nigeria’s innovation community. He said the response demonstrated both capacity and determination.
Three entries made the final shortlist:
1. GenScan AI (GenMRI/C-MORE) by Mary-Brenda Akoda
2. EwaDx Smart Bra Diagnostic Device by Kemisola Bolarinwa
3. Accuracy and Reliability of MedBrain in Assisting Triage and Diagnosis of Common Acute Paediatric Conditions in Ethiopia, by Pol Ricart and Paul Dinwoke
Each, Nnaji said, demonstrated ingenuity and a propensity for solving real problems. Only one scored highest against the approved criteria — scientific novelty, technical soundness, developmental impact, scalability and practical application.
The panel of judges, chaired by Dr Omobola Johnson (Senior Partner, TLcom Capital LLP, who was unavoidably absent from the announcement), included Professor Aminu Muhammad Bui of Usmanu Danfodiyo University, Sokoto, and Professor Collins Udanor Nnalue of the University of Nigeria, Nsukka. Their recommendation was unanimous; the Advisory Board endorsed it.
“If an entry is declared worthy of the Prize today, we can be confident that it has earned that distinction through a thorough and credible evaluation process,” said Dr Sophia Horsfall, General Manager, External Relations and Sustainable Development, NLNG
Horsfall presented the 2026 winner as proof that the prize’s standards had not been lowered since 2025. Standards, she said, remained uncompromising; what had changed was the quality of the work submitted to those standards.
Why the judges chose software over steel
Magnetic Resonance Imaging (MRI) is slow, scarce and expensive. Long acquisition times mean fewer patients per machine, longer waiting lists, more sedation for children or anxious patients, and delayed diagnoses. A 2016–2018 survey published in the Pan African Medical Journal reported Nigeria’s installed MRI fleet at 58 machines; no single official, up-to-date public database confirms the true number of functional units. Either way, capacity is thin relative to need.
GenScan AI does not add machines. It aims to make the ones already installed work harder. Its C-MORE algorithm uses a one-step consistency model framework to reconstruct high-quality images from far less acquired data. Hospitals would not need new scanners — only software on compatible existing hardware. In principle, a 20-minute scan could be reduced to about two minutes. Throughput rises; wait lists shrink; earlier diagnosis becomes more plausible, especially in resource-constrained systems.
That combination — advanced generative AI with a deployable healthcare use case — was described by the judges as the strongest blend of innovation, technical depth and developmental relevance among the shortlisted works. Nnaji was explicit about the prize’s founding purpose: not novelty for its own sake, but work that can improve lives using the infrastructure Nigeria already has.
“GenScan AI stood out for combining advanced artificial intelligence with a practical healthcare application that could improve the efficiency and accessibility of medical imaging,” said Professor Barth Nnaji, Chairman of the NPSI Advisory Board.
The researcher behind the reconstruction
Akoda’s path to the prize is unusually linear for someone still in her late twenties. She holds First-Class Honours in Computer Science from Goldsmiths, University of London, and an MRes with Distinction in Artificial Intelligence and Machine Learning from Imperial College London, where she was a Google DeepMind Scholar. Her Imperial research focused on deep generative models for MRI reconstruction — the same problem that C-MORE now addresses in product form — and was supported by a Fetch.ai Compute Award in February 2025.
Before founding GenScan AI, she worked as a software engineer and AI research scientist at Microsoft, including at the Mixed Reality and AI Research Lab in Cambridge. An earlier internship involved using deep learning to animate 3D human avatars from video and audio. She also helped establish Microsoft’s GOL Clinics West Africa programme, which provides training in .NET, JavaScript, Git, Azure and software design to 120 young people across the region.
The prize is not her first public recognition, nor is MRI her first attempt to bring AI into a clinical setting. Earlier work includes patented AI for diabetic retinopathy detection in Nigeria; Amazing Matriarchs, a children’s book about women inventors; Grassroot Solar, which brings solar energy to rural communities; and Drone ER, a security-driven emergency-response concept that won first place in the 2021 Nigeria Drone Business Competition while she was at the African Leadership Academy in South Africa.
More recently, Mary-Brenda Akoda has been gathering grants and lists:
1. Founderland Forward Grant (Q4 2025): a $10,000 award recognising the MRI-acceleration thesis.
2. A Social Innovation Award in May 2026, with a £10,000 grant;
3. Innovate UK recognition in August 2026, naming her among 100 women founders shaping the UK’s future industries, with language stating that the work could “speed up diagnosis, reduce NHS waiting lists, and improve care for millions of patients.”
The biographical notes that accompanied the prize materials also identify a personal motive: an innovation “born of personal tragedy and a determination to prevent others from suffering delayed diagnoses.” The official announcement doesn’t elaborate on that claim, but it is the emotional through-line of the profile documents: a Nigerian woman building clinically relevant generative AI, from early social-impact projects through Microsoft and Imperial to a MedTech company whose selling point is that diagnosis need not wait for a new scanner.
What winning is — and is not
A prize of this size is a signal, not a deployment. GenScan AI still has to prove itself on hospital floors: securing regulatory clearance, ensuring hardware compatibility, validating image quality against radiologists’ standards, and undertaking the unglamorous work of integrating software into machines that already have their own waiting lists. The judges scored potential and technical soundness; they did not, and could not, certify a national rollout.
What they certified is a bet Nigeria’s flagship science prize is willing to make in public: that the next increment in MRI capacity may come from algorithms rather than import orders, and that a millennial founder from Cross River State, trained in London and Cambridge, is a credible person to make that bet.
NLNG congratulated every 2026 entrant on the same grounds — that submissions themselves strengthen the country’s scientific and innovation ecosystem, whether or not they take home the cheque.
On 9 October, Akoda will walk onto a stage to collect US$100,000. The more consequential test begins after the photographs: whether a 20-minute scan can, in enough Nigerian rooms, become a two-minute one — and whether the patients who have been waiting the longest notice first.
