LIDA Data Scientists Win Double at Digital Footprints 2026

Data Scientists from the Leeds Institute for Data Analytics (LIDA) have achieved outstanding success at this year’s Digital Footprints 2026 conference, securing two prizes across highly competitive categories for early career researchers. The conference brings together academics, policymakers and industry leaders to explore how data science can address challenges in digital society.

The conference featured two presentation formats, flash talks and posters, and recognised excellence through three prize categories: Best Early Career Researcher (ECR) Flash Talk, Best ECR Poster, and Best Poster of the Conference, the latter voted for by delegates.

LIDA researchers were recognised in two of these categories, with both awards including funding to support career development and future conference participation, highlighting the institute’s strength in delivering impactful, real-world data science across diverse domains.

Best Poster of the Conference (Delegate Vote)
Molly Sargent

Molly Sargent, Data Scientist, was awarded the Best Poster of the Conference prize, as voted by attendees, for her project: “When Deprivation Doesn’t Tell the Whole Story: Comparing Measures of Need and Evaluating Food Policy Equality”. The work represents Molly’s first project led by Alice Kinninmonth, Research Fellow in Nutrition and Lifestyle Analytics at the School of Food Science & Nutrition.

Reflecting on her success, Molly said: “Winning the best poster prize was completely unexpected and genuinely overwhelming, in the best possible way. What I'm most proud of is that this project started as a research question about measurement and became something practically useful: a tool that makes complex data accessible to people making real decisions about where support is needed. The idea that a policymaker or local authority could explore how deprivation looks different depending on the lens you use, without needing specialist data skills, feels meaningful. I hope it encourages more people to ask which measure they're using and why it matters.”

Alice Kininmonth said, "This interactive dashboard supports a more nuanced understanding of area-level need. By enabling users to explore and compare the Priority Places for Food Index and Index of Multiple Deprivation across neighbourhoods in England, it shows where the two measures align and where they diverge. This matters because these indices capture different dimensions of need, and do not always highlight the same areas as priorities for support. By making these patterns accessible for users without specialist data skills, this tool supports policymakers and practitioners to make evidence-based decisions, identify areas that may otherwise be overlooked, and direct resources and interventions where they are most needed."

Highly Commended ECR Flash Talk
Piyush Mohan

Piyush Mohan, Data Scientist, received the Highly Commended award in the Best ECR Flash Talk category for his presentation on "Interpretable AI for Pedestrian Intention Prediction: A Data-Driven Visualisation Approach". The project was led by Mahdi Rezaei, Associate Professor at the Institute for Transport Studies.

Piyush Mohan said: “Winning the Highly Commendable ECR award was a great experience. I'm thankful for the chance to work on the project and for the opportunity to disseminate findings to such a diverse audience. I'm glad I was able to share the project's message in a way that the panel and audience felt connected to. During the conference, several individuals shared their concerns and interests in the work around pedestrian safety and automated systems. Being able to start a discussion on such topics through the project made me feel really proud of the work my team and I were able to achieve.”

Mahdi Rezaei added: “This project represented an important step towards more transparent and trustworthy AI for autonomous vehicles and intelligent transport systems. By improving our understanding of how models such as PIP-Net interpret pedestrian behaviour and environmental cues, we can build greater confidence in AI-assisted decision-making. In the long term, these advances could contribute to safer vehicles, more effective human–machine interaction, and wider public acceptance of autonomous technologies, ultimately supporting the deployment of safer and more intelligent transport systems worldwide.”

Together, these award-winning projects demonstrate LIDA’s breadth of expertise, from developing practical tools to support policymakers in addressing social inequality, to advancing cutting-edge AI research that can improve safety in real-world environments.

These achievements highlight the strength of LIDA’s interdisciplinary research community and its commitment to producing data-driven insights that address pressing societal challenges.