Mahmud Tantoush

Mahmud Tantoush serves as a Senior Lecturer at the Manchester School of Architecture, Manchester Metropolitan University, where he leads the Complexity, Planning and Urbanism (CPU) Master of Architecture Year 1 studio and teaches Advanced Digital Design across undergraduate and postgraduate programs. As a core researcher with the Complexity, Planning and Urbanism Lab (CPU-Lab), he directs computational urbanism initiatives at the Manchester Technology Centre.

His research integrates Urban Big Data and urban morphology to decode city experiences across spatial-temporal scales, with specialization in smart cities, crowdsourced urban analytics, geographic data science, and complexity theory. Methodologically, he pioneers computational design frameworks using BIM, GIS, parametric modeling, and programming applications, particularly focusing on social media data (Twitter) as urban sensors. Key thematic threads include hybrid urban-digital spaces, mobility futures, and emergent patterns in city functioning.

Analysis of his 15 most recent publications (2025-2019) reveals three dominant trajectories: (1) spatiotemporal pattern recognition in urban dynamics using social media feeds, (2) participatory co-design of mobility systems through backcasting techniques, and (3) theoretical bridging of agent-based modeling with big data for complex urban systems. His work consistently applies complexity theory to real-world urban challenges across global contexts from Libya to Greater Manchester.

Tantoush has secured significant research funding including the SASSI project (2019-2022) addressing sustainable sanitation in China and the MaaS Prototype for Transport for Greater Manchester (2021-2022). He leads the CPU-Lab's interdisciplinary team developing computational tools for urban analytics, with current focus on real-time data integration for adaptive city planning. His Arabic/English bilingual capabilities enhance cross-cultural urban research collaborations.