Dr Yahya Gamalaldin
- Research Associate (Urban Big Data)
Biography
Yahya Gamal is a Research Associate in the Artificial Intelligence for Collective Intelligence (AI4CI) hub, and he is based in the Urban Big Data Centre (UBDC), University of Glasgow (UofG). He initially joined the UBDC in July 2023 as a Research Associate in computational social simulations, particularly agent-based models.
Prior to this, Yahya Gamal did a PhD in the University of Manchester. His PhD focused on simulating market procedures and residential location choices using agent-based models. He was also a Research Assistant between April 2022 and April 2023 in the Tomorrow's Cities project in both University College London and King's College London. He contributed to developing agent-based models to test the effect of road network development for flood resilience on land prices and gentrification.
Yahya Gamal has also been involved in teaching roles in Cairo University, Salford University and the University of Manchester. His teaching involved GIS tools, town planning and decision support systems for urban developers (using agent-based models).
Research interests
Research and Methods
My research interest lies in computational social simulations of geographical urban systems. I am keen to use social simulations to understand urban systems and to comprehend the underlying reasons for different spatial phenomenon.
I am particularly interested in the following topics and methods:
- Agent Based Models (ABMs) as tools to simulate decisions that lead to spatial outcomes
- AI methods coupled with ABMs, including Artificial Neural Networks (ANNs) as ABM emulators
- Uncertainty Quantification (UQ) of ABMs spatial outcomes
Research groups
Grants
2026-2029 EPSRC Doctoral Studentship Supervisor-Led Project 'Using ML and individual-based modelling to create resilient urban mobility'. Role: co-supervision
The PhD project extends on work applied in the AI for Collective Intelligence (AI4CI) - AI Hub led from the University of Bristol. Funded by EPSRC for 5 years. The project focuses on developing an agent-based modelling framework integrateing synthetic population generation, activity-based demand modelling, and multi-modal routing (walking, cycling, car, and bus) on realistic transport networks. Crucially, it introduces dynamic schedule adaptation.
Supervision
- Daniel Konioukhov: Exploring the uptake of Autonomous Vehicles (AVs) and the impacts of their networks on transport and mobility systems
Teaching
URBAN5160 Advanced Topics for Urban Analytics: Module focusing on agent-based modelling methods. Includes critically analysing and building agent-based models
PUBPOL4044 - Big Data, Policy & Power: Guest lectures focusing on smart cities and urban simulations
Professional activities & recognition
Selected international presentations
- 2025: Social Simulation Conference (Delft, Netherlands)
- 2025: CUPUM (London, UK)
- 2022: Dynamic Days Europe 2022 (Aberdeen, UK)
- 2021: ECTQG (Manchester, UK)
- 2019: AESOP 18th Meeting: Games for Cities (Lisbon, Portugal)
