Recent N/LAB Projects

Big Data for Resilience – Flooding in Dar es Salaam

Dar es Salaam suffers from biannual flooding caused by various factors including climate change and rapid unplanned urban growth. Receiving a ESRC-NERC-DFID grant for “Big Data for Flood Resilience in East Africa”, this project investigates […]

Transport – Road Conditions

Leveraging recent deep learning advances with high resolution drone imagery, the team has developed state-of-the-art techniques for the automatic detection of buildings and roads from aerial imagery. N/LAB is now focusing on the extension of […]

Community Mapping

Maps are crucial in emerging countries to make decisions, but often do not exist. Community mapping is a participatory process where community members map their neighbourhoods, making maps openly available in the process. In emerging […]

Refined Limit on the Predictability of Human Movement

It has been recently claimed that human movement is ‘highly predictable’ upper bound of 93% predictability shown. However, knowing an upper bound is only useful if it is relatively tight, i.e. it is close to the […]

Data Donation for Public Good

How could donated data help our society? Data is a rich source of people’s habits – shopping data from loyalty cards, for example, can reflect our diet. If people donate their personal data for research, […]

Dynamic Topic Modelling for Consumer Segmentation

The importance of meaningful segmentation of consumers from a retail perspective cannot be overstated. Current approaches, however, oversimplifies the situation, most notably by aggregating away time, conflating behaviour based on temporal differences – despite the […]

PARM – Projection Augmented Relief Models

The Projection Augmented Relief Model (PARM) system is an award winning new display system that provides a physical, 3-Dimensional approach to data visualization. Using digital projection onto physical models in combination with a dynamic display […]

Towards Optimal Symbolisation of Time Series Data

Time series symbolisation is a common pre-processing step to speed up computation, reduce storage costs and/or enable the application of certain algorithms. In this work we show that current symbolisation techniques are sub-optimal in (at least) […]