Uudised

Meet John: Turning AI predictions into decisions people can trust

Published on 17.09.2026

Written by FinEst Centre for Smart Cities

From Malawi to Finland and now Estonia, John Patrice Matekenya’s research journey has been driven by one central question: how can artificial intelligence create real value for the people who use it?

As a PhD researcher at Aalto University and visiting researcher at the FinEst Centre, John is exploring how explainable AI can support preventive maintenance in critical urban infrastructure while making AI predictions clear, trustworthy and useful for decision-makers.

Drawing on experience in data science, AI for social good and technology development across the Global South, he brings both a technical and human-centred perspective to smart city research.

In this article, he shares his research journey, what draws him to explainable AI and his experience at the FinEst Centre.

Could you share more about your work, background and your research area and interest?

I’m from Lilongwe, the capital of Malawi; fondly known as the warm heart of Africa. I’m a PhD researcher at Aalto University in the Department of Industrial Engineering and Management, where I focus on co-designing explainable machine learning for social good in low-resource contexts. I studied computer science at the University of Malawi’s Chancellor College and later earned an MSc in Data Science and Artificial Intelligence from Bournemouth University as a recipient of the prestigious Chevening Scholarship.

My professional life has been a canvas for exploration, with a steady focus on building solutions that improve quality of life and service delivery across the global south.

From consulting for the World Bank and USAID to co-founding a tech startup, Apalis in 2018, I’ve consistently sought out daunting challenges and tried to build moonshot innovations to meet them. My interests sit at the intersection of AI for good, AI literacy and usability, and embedding explainability into the AI-powered solutions that make smart cities work.

What are your main research topics and what draws you to these topics?

At the FinEst Centre for Smart Cities, I research how AI can reduce equipment failures in critical infrastructure such as energy systems and HVAC units by strengthening preventive maintenance. I build predictive models and software that help catch faults early, before they become costly breakdowns. But the part I care about most is closing the gap between what an AI model predicts and how that prediction actually gets used. That’s where social explainability comes in.

I’m also curious about a related question: how can machine learning predictions be designed so they don’t overwhelm the people relying on them, but instead give those people better tools to do their work? I’m excited to be working with Dr. Avleen Malhi and to contribute to the ongoing research happening here in smart cities.

How does your research connect to smart cities?

Today, buildings, roads, cars, and countless other things are continuously generating and consuming data. Artificial intelligence has surged forward on the back of all this data, but as more and more AI solutions are deployed to improve services and lives, the effort to make those solutions explainable deserves just as much emphasis.

In a smart city, AI advice should be easy to understand: clear, traceable, and transparent enough that people actually trust it and act on it. This is the gap my research sets out to close.

What do you like to do outside work and research?

Outside work, I enjoy hiking, playing social football, and singing in a vocal jazz ensemble called Cadence. I’ve found long trails to be therapeutic as they tend to spark new ideas, and often, a good photo or two. Music has always been my creative outlet; writing and performing bring me real joy.

What do you hope to gain from the experience of working at the FinEst Centre?

Coming from a technical background, I’m excited to collaborate with people from different fields and to extend my work on AI usability beyond models into the world of policy.

Working in a dynamic, interdisciplinary team like the one here at the FinEst Centre will sharpen my expertise in AI and data policy. And I hope my involvement with TalTech in Estonia will open opportunities for collaboration between Estonia, the EU, and Malawi across AI, technology policy, and smart cities.

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