Students win £5000 in data sciences challenge

14 January 2022

This year, three Oxford postgraduate students  – including Jesus College’s Munib Mesinovic – took part in a global data science hackathon for university students around the world, winning the second prize of £5,000.

Natalia Hong (Keble College), Jiazheng Zhu (Lady Margaret Hall), and Munib are all first-year postgraduate students on the Centre for Doctoral Training Health Data Science course. Munib writes about their experience in the challenge in this Student Spotlight article, first published on the Oxford Students website.

The journey so far

We all come from different countries with Natalia coming from Malaysia, Jiazheng from China, and myself from Bosnia and Herzegovina. We met on the first year of our course and what brought us to apply for the Hackathon was thinking about how to further contextualise the knowledge we were gaining in our studies, while also challenging ourselves.

Natalia, Munib and Jiazheng celebrate their £5000 2nd Prize in the Huawei Hackathon


The annual Huawei Hackathon involves developing software to improve Wi-Fi services to be both sustainable and adaptable. The challenge consisted of two tasks, with a final presentation of solutions. Our solution was praised for its innovativeness and durability to testing, ranking first on the leaderboard and completing second overall.


We are all grateful to the vital support we received from our mentors and loved ones.

Making an impact in Oxford

Besides my studies, I have tried to dedicate my time to making an impact here in the Oxford community and exploring the wider context of my work in AI. To that end I co-founded the Oxford Diplomatic Society and this year I will be joining the Global Leadership Initiative at the Oxford Character Project.

The ethical considerations of AI have also been important to me which is why I was involved as a member in Mozilla Foundation’s Working Group on Building Trustworthy AI last year.

Looking to the future

As all of us are currently in the first year of our doctoral studies and are excited to be able to apply our background knowledge in statistics and mathematics to solving the complex challenges in healthcare with the help of AI.

For myself, that means using machine learning to tackle challenges of cardiovascular disease, fore-mostly prediction of acute myocardial infarctions (heart attack) as a leading cause of death which my family and so many others have directly suffered from. Our hope is that our interdisciplinary work combining computer science and medicine in a responsible and ethical manner can greatly alleviate the health challenges of the 21st century.

With thanks to Lauren Gale for allowing us to reproduce this article.