UCL Computer Science is playing a central role in the most recent round of funding from the UCL Grand Challenges under the Data Empowered Societies (DES) programme. Four projects led or co-led by UCL Computer Science staff will now join a broader portfolio of ten interdisciplinary DES awards made across UCL for 2025–26 and 2026–27.
These projects span sustainability, humanitarian insight, AI-supported work, and environmental monitoring.
What is the UCL Grand Challenges programme?
UCL Grand Challenges is a university-wide programme that brings researchers together across disciplines to tackle pressing global issues. It provides seed funding and a framework for collaboration so that experts from different fields can work jointly on problems that have real-world impact.
Data Empowered Societies (DES) is one of the Grand Challenges themes. It focuses on how data and digital technologies can be used in inclusive, responsible ways to improve people’s lives, inform better decisions and support fairer, more sustainable societies.
UCL Computer Science–led Projects
AI and Human-Job Matching (AI‑MATCH)
Lead: Dr Maria del Rio-Chanona (UCL Computer Science)
Co-lead: Dr Suphanit Piyapromdee (Social & Historical Sciences / Economics)
AI-MATCH explores why individuals with similar backgrounds can experience markedly different outcomes when working with AI tools. Through experiments with UCL students, the project will analyse variation in performance, interaction styles, prior skills and behavioural factors. Insights will support future thinking on education, training, and equitable use of AI in work and study.
RiverGuard: Proactive Sensing and Rapid Response for Urban Water Quality
Co-leads: Dr Valerio Modugno (UCL Computer Science) and Dr Izzy Bishop (Life Sciences)
RiverGuard brings together data, sensor technologies, drones, aquatic robotics, and open data sources to build an early-warning and rapid-response system for monitoring water quality in urban rivers.
The goal is to detect and respond quickly to pollution events, which may be brief and highly local, offering a richer, more responsive alternative to traditional periodic monitoring.
AI for Good and Migration Dynamics
Co-leads: Professor Benjamin Guedj (Computer Science) and Dr François Sicard (Arts & Humanities)
This project will use data-driven modelling and probabilistic techniques to better understand migration dynamics across the Channel, with the aim of informing humanitarian response and policy planning.
The research applies advanced computational and statistical methods to a deeply human and socially significant challenge.
Forecasting Energy Demand to Cut Costs and Emissions
Leads: Professor Maarten Speekenbrink (Experimental Psychology),
Co-leads: Professor Benjamin Guedj (UCL Computer Science) and Professor Duncan Wilson (The Bartlett Centre for Advanced Spatial Analysis)
This Data Empowered Societies Living Lab project will use UCL’s extensive smart-meter data to develop predictive tools that forecast energy demand, detect anomalies, and identify opportunities to reduce unnecessary usage across the university estate.
The team will build a machine-learning model and a real-time dashboard to support Estates and Sustainability Services, with behavioural-science interventions developed in collaboration with students.
Contributing to UCL’s DES vision
Under the leadership of Pro-Vice-Provosts Allison Littlejohn and James Hetherington, the DES programme is shaping a vision of human-centred data innovation across UCL, bringing together research, education, professional services and real-world partners.
These four UCL Computer Science projects contribute to that wider effort by applying the department’s technical strengths to social, environmental and economic challenges, forming part of a growing body of work using data to support practical solutions for people and communities.
Further information
Dr Maria del Rio-Chanona on UCL Profiles
