About

Full CV and pdf download can be found here.

Summary Link to heading

Carrow is a doctoral researcher at Newcastle University, supported by the Defence Science Technology Laboratory ((DSTL)) and the Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training in Geospatial Systems. His doctoral research is centered on pioneering advanced artificial intelligence systems for predicting complex spatiotemporal dynamics within urban environments. This work leverages near real-time geospatial data from Internet of Things (IoT) sensor networks to address critical challenges in urban monitoring and situational awareness.

His investigation specifically explores the development and application of deep-graph neural networks (GNNs) capable of forecasting urban phenomena using data from sparse sensor networks. A key aspect of his work involves critically examining how various dimensions of data quality influence the performance of predictive models, with a particular focus on applications such as pedestrian monitoring. This research delves into the integration of deep learning methodologies with agent-based modelling (ABM) to effectively simulate and understand intricate spatiotemporal dependencies inherent in urban sensor data.

As an emerging researcher in urban analytics, Carrow has disseminated his findings at prominent academic conferences, including GISRUK (GIS Research UK) and CUPUM (Computational Urban Planning and Urban Management). His doctoral contributions are geared towards advancing digital twin technologies. The overarching goal is to foster the development of more resilient, safer, and sustainable urban environments by enhancing real-time decision support systems, particularly for applications in security and emergency response scenarios. This work aims to provide pathways for making urban data ‘AI ready’ and to demonstrate the value of data collected by centralised urban repositories for improved decision-making.

PhD Link to heading

Title: Real-Time Prediction of Spatiotemporal Dynamics in the Built Environment: An AI and Internet of Things Approach.

Proposal Page

Qualifications Link to heading

PhD in Digital Twins for Urban Systems | Geospatial Systems CDT (Newcastle University) | (in progress)

Geospatial Data Science MRes | Newcastle University School of Engineering | Distinction

Civil and Structural MEng | Newcastle University School of Engineering | 1st Class Honours