2025 Projects
The Hour of Need: The Illusion of Time
In partnership with Energy UK
We leveraged the time-use survey data and the SERL (Smart Energy Research Lab) smart meter records from the UK Data Services, which were all anonymised. The time-use survey is an annual survey of randomly selected households across the United Kingdom. We used the 2023 survey, which contained over 2000 nationally representative households across the UK with information on several activities they carried out indoors and those outdoors, the time of use, and the demographic details of the households, such as age, employment, annual household income, housing tenure.
By Emeka (Buchi) Enechukwu
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Wheely Easy: Creating a Wheelability Network for Bradford
In partnership with Healthy Urban Places, Population Health Improvement UK and University of Bradford.
Cities may appear easy to navigate, but for wheelchair users, everyday journeys are often shaped by barriers that most people never notice. Urban accessibility research has long focused on walkability, assessing how easily people can move through cities on foot. However, this perspective often assumes an able-bodied pedestrian and overlooks the specific challenges faced by wheelchair users. As a result, streets that are considered accessible in conventional assessments may still present significant barriers for those relying on wheeled mobility.
By Chenrui Xiao
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Towards a Geospatial Foundation Model for Mobility
In partnership with Geolytix
Every day, millions of people move through cities in patterns so routine that we barely notice them. Understanding and predicting human mobility is central to urban analysis, city planning, transport and land-use management, and a wide range of applications in public policy, business location research, commercial site selection, retail network planning, and public service delivery.
By Damilola Ogungbemi
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Patterns in Complex Care Needs: Understanding how Musculoskeletal conditions shape healthcare utilisation for patients with Multiple Long-term Conditions in Leed
In partnership with NHS West Yorkshire Integrated Care Board
Approximately one in four adults in the UK live with more than one long-term condition. Managing multiple conditions can be complex, time consuming, and often inefficient. But what about those patients who also experience musculoskeletal disorders? With added burdens of mobility issues, daily pain, and conflicting health needs, it can be difficult for these patients to access the care they need, when they need it.
By Emma Briggs
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Machine Learning Methods for Rapid Cyber Incident Response
In partnership with a confidential partner
Investigating the causes of an attack and tracing the actions of the attacker is the critical first step in responding to an incident. This investigation work is highly technical and complex, requiring expert, highly-trained staff whose skills are in exceptionally high demand. These staff pore over huge pools of unstructured data searching for the needle in the haystack which indicates what an attacker has done and how they have done it.
By Hal Kolb
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Evaluating the impact of cultural events using machine learning and digital footfall: a case study of Bradford City of Culture 2025
Beyond the box office: can AI redefine cultural evaluation by measuring how culture moves a city? Cultural events are hugely important to communities, yet the UK’s arts, culture and heritage sector struggles to evidence their social, civic and economic value. This project aimed to evaluate the success of the Bradford City of Culture 2025 programme, by using machine learning to investigate changes in footfall patterns across the Bradford district, assessing both immediate effects and potential longer-term legacy outcome.
By Marion Carneiro
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When Deprivation Doesn’t Tell the Whole Story: Comparing Measures of Need and Evaluating Food Policy Equality
Change the measure, and you can change the conclusions we draw. This is a challenge when trying to identify people in need of support. The metrics we use to define ‘need’ can shape both who is identified as a priority for receiving support and how we judge whether national policies have an equitable impact. This project examines how measurement choice shapes both where it is important to provide additional support and how we evaluate the equitability of national policy.
By Molly Sargent
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Interpretable AI for Pedestrian Intention Prediction: A Data-Driven Visualisation Approach
As vehicles move towards full autonomy, AI models are increasingly trusted to predict pedestrian behaviour and make split-second safety decisions. Yet the black-box nature of these models makes failure cases hard to diagnose, where one wrong prediction separates a safe stop from a possible collision. This project demonstrates how visual analytics can be applied to explain such critical decisions made by complex AI models.
By Piyush Mohan
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