Annual Methods Lecture 2025 - Durham University

The Christine Merrell Annual Methods Lecture 2025

DRMC's annual methods lecture, in honour and memory of Professor Christine Merrell, who was a Professor of Education and Deputy Executive Dean (Research) for the Faculty of Social Sciences, will be taking place on:

Tuesday 20th May 2025 at 5pm

The Lecture is titled 'Learning the City: AI-Driven Approaches to Complexity' by Professor Alison Heppenstall, Professor of Geocomputation at the University of Glasgow and Durham University Alumni.

The lecture will be followed by a Q&A session and the DRMC Picturing Research Competition Winners will be awarded.

This is a face-to-face lecture.

There will be a drinks reception and dinner after the lecture at Hotel Indigo, Durham from 6.30pm (dinner will be allocated on a first-come-first served basis).

Click Here to register for this event

The closing date to complete this form will be Tuesday 6th May 2025, 6pm.

Lecture Abstract

Cities are complex, dynamic systems shaped by human behaviour, infrastructure, and policy. As urban areas face mounting challenges—from climate change and congestion to housing and inequality—AI and machine learning offer alternative tools to analyse, simulate, and inform decision-making at scale. This talk explores how emerging methods, including synthetic data generation, geospatial machine learning, and agent-based modelling, are transforming urban analytics. By combining real and synthetic datasets, we can build more robust and accurate models that support smarter urban planning, mobility forecasting, and public service delivery. This talk will use examples from current work to highlight the potential of AI-driven urban intelligence to create more equitable and resilient cities.

Biography of Speaker

Speaker	Biography
	Alison's undergraduate degree was in Archaeology at Grey College, University of Durham. She was always fascinated by the emergence of culture, interactions and movements of past populations. It seemed inevitable that after encountering programming and Geocomputation during her Master’s at the University of Leeds, she fell into a PhD that created and developed agent-based models for empirical applications. Alison was lucky enough to have subsequent EPSRC and ESRC Fellowships focused on the building of Machine Learning/Artificial Intelligence approaches such as neural networks, evolutionary algorithms, agent-based modelling, microsimulation, data assimilation and uncertainty quantification etc. Whilst at the University of Leeds, she was involved in the Leeds Institute for Data Analytics, Consumer Data Research Centre and the Urban Analytics Programme at the Alan Turing Institute. Alison held the inaugural ESRC-Turing Fellowship and was awarded the International Society of Computational Economics prize for “outstanding contribution in computational social simulation” from the Italian Research Council in 2022. She is a member of the DSAB at the Joint BioSecurity Council and a member of the Royal Geographical Society. She is a current Alan Turing Fellow. Alison is a methodologist - she is interested in adapting and developing AI/ML approaches to solving problems in different domains. She has extensive experience with spatial agent-based models, microsimulation, evolutionary approaches as well as strong interests in uncertainty quantification, reinforcement learning and data assimilation. She is also interested in the development of exascale computation for application in the social sciences. This ties into an ongoing agenda of creating urban digital twins that she is involved with at local and national level.

Speaker

Biography

Alison's undergraduate degree was in Archaeology at Grey College, University of Durham. She was always fascinated by the emergence of culture, interactions and movements of past populations. It seemed inevitable that after encountering programming and Geocomputation during her Master’s at the University of Leeds, she fell into a PhD that created and developed agent-based models for empirical applications.

Alison was lucky enough to have subsequent EPSRC and ESRC Fellowships focused on the building of Machine Learning/Artificial Intelligence approaches such as neural networks, evolutionary algorithms, agent-based modelling, microsimulation, data assimilation and uncertainty quantification etc.

Whilst at the University of Leeds, she was involved in the Leeds Institute for Data Analytics, Consumer Data Research Centre and the Urban Analytics Programme at the Alan Turing Institute. Alison held the inaugural ESRC-Turing Fellowship and was awarded the International Society of Computational Economics prize for “outstanding contribution in computational social simulation” from the Italian Research Council in 2022. She is a member of the DSAB at the Joint BioSecurity Council and a member of the Royal Geographical Society. She is a current Alan Turing Fellow.

Alison is a methodologist - she is interested in adapting and developing AI/ML approaches to solving problems in different domains. She has extensive experience with spatial agent-based models, microsimulation, evolutionary approaches as well as strong interests in uncertainty quantification, reinforcement learning and data assimilation. She is also interested in the development of exascale computation for application in the social sciences. This ties into an ongoing agenda of creating urban digital twins that she is involved with at local and national level.