Conference Programme

Research Centres

The full programme will be available here as soon as it is finalised.

Broad programme:

	Mon 24 Aug	Tue 25 Aug	Wed 26 Aug	Thu 27 Aug	Fri 28 Aug
Morning	Workshops	Welcome Keynote: Lasse Gerrits	Keynote: Kayla de la Haye Parallel sessions	Keynote: Iris Lorscheid Parallel sessions	Keynote: Dave Byrne Parallel sessions Awards Close
Afternoon	Workshops	Parallel sessions	Parallel sessions	Parallel sessions ESSA meeting	Conference ends at lunch time
Evening		Drinks reception	Conference Dinner

Mon 24 Aug

Tue 25 Aug

Wed 26 Aug

Thu 27 Aug

Fri 28 Aug

Morning

Workshops

Welcome

Keynote: Lasse Gerrits

Keynote: Kayla de la Haye

Parallel sessions

Keynote: Iris Lorscheid

Parallel sessions

Keynote: Dave Byrne

Parallel sessions

Awards

Afternoon

Workshops

Parallel sessions

ESSA meeting

Conference ends
at lunch time

Evening

Drinks reception

Conference Dinner

Keynote Speakers

Your keynote speakers for the conference are:

Dr Lasse Gerrits, Erasmus University, Rotterdam

Lecture Title - Liminal Imagination in Social Simulation

Speaker	Lecture Abstract
	Social simulation can be extremely powerful when it comes to understanding complex social dynamics. At the same time, simulation can become a straightjacket where technical refinement takes priority over big questions. While such refinements are needed, they should not replace our capacity to see the social real in new and provoking ways. Are there ways in which we can drive our curiosity to ask new questions when simulating the social? This lecture calls for a liminal imagination in such simulations. Liminal imagination concerns the creative capacity that emerges in liminal spaces—transitional, in between moments, or environments where ordinary structures, routines, or identities are temporarily suspended—allowing the mind to form novel associations, ideas, and narratives. It is also the mental flexibility to feel at home with not-being-at-home; to dwell in threshold spaces in between defined states, categories, and realities; to embrace the undefined. Simulations can be excellent liminal spaces, but it requires effort to get there. I’ll talk about the ways in which we can put those simulations to good use.

Speaker

Lecture Abstract

Social simulation can be extremely powerful when it comes to understanding complex social dynamics. At the same time, simulation can become a straightjacket where technical refinement takes priority over big questions. While such refinements are needed, they should not replace our capacity to see the social real in new and provoking ways. Are there ways in which we can drive our curiosity to ask new questions when simulating the social? This lecture calls for a liminal imagination in such simulations. Liminal imagination concerns the creative capacity that emerges in liminal spaces—transitional, in between moments, or environments where ordinary structures, routines, or identities are temporarily suspended—allowing the mind to form novel associations, ideas, and narratives. It is also the mental flexibility to feel at home with not-being-at-home; to dwell in threshold spaces in between defined states, categories, and realities; to embrace the undefined. Simulations can be excellent liminal spaces, but it requires effort to get there. I’ll talk about the ways in which we can put those simulations to good use.

Professor Dave Byrne, Retired Professor of Durham University

Lecture Title - Is Simulation still a Way Forward for the Social Sciences?

Speaker	Lecture Abstract
	Nearly 30 years ago I wrote a piece for Sociological Research Online entitled: ‘Simulation - A Way Forward?’ One thing I will do in the closing plenary is reflect on how what I have heard and seen informs an answer to that question today, but here are some things to note which whilst I do believe in the great potential value of simulation as a tool of social science still at this point remain issues for me given that like Paul Cilliers I believe that modelling complex systems is impossible but nevertheless we have to model them: getting beyond a micro-emergent account; developing an understanding of the role of social structures which gives them causal powers; enabling an account of how power works in relation to the capacity of agents to shape social structures; writing nature and its power into our simulations.

Speaker

Lecture Abstract

Nearly 30 years ago I wrote a piece for Sociological Research Online entitled: ‘Simulation - A Way Forward?’ One thing I will do in the closing plenary is reflect on how what I have heard and seen informs an answer to that question today, but here are some things to note which whilst I do believe in the great potential value of simulation as a tool of social science still at this point remain issues for me given that like Paul Cilliers I believe that modelling complex systems is impossible but nevertheless we have to model them: getting beyond a micro-emergent account; developing an understanding of the role of social structures which gives them causal powers; enabling an account of how power works in relation to the capacity of agents to shape social structures; writing nature and its power into our simulations.

Professor Dr Iris Lorscheid, University of Europe for Applied Science, Hamburg Campus

Lecture Title - From Model to Actor: AI Agents and the Social Turn of Artificial Intelligence

Speaker	Lecture Abstract
	Artificial intelligence is undergoing a profound transformation. For much of its history, AI systems functioned primarily as analytical models: they classified images, predicted outcomes, or detected patterns in data. Today, however, a new generation of systems is emerging. AI agents built on large language models can plan tasks, access tools, interact with data environments, and coordinate actions across digital systems. In this shift, AI is moving from model to actor. This transformation has far-reaching implications. As AI systems begin to act autonomously in digital infrastructures—interacting with humans, organizations, and other agents—they become embedded in complex social systems rather than merely analysing them. Recent developments in AI agent architectures illustrate this transition. By combining large language models with memory, planning mechanisms, and tool access, AI agents are able to pursue goals, interact with data sources, and execute sequences of actions across digital environments. These capabilities blur the traditional boundary between analytical models and operational decision systems. Rather than viewing AI purely as a technological capability, we may need to understand it as a new class of actors embedded in socio-technical systems. This perspective opens a new research frontier for computational social science: studying and shaping societies in which human and artificial agents increasingly interact, collaborate, and co-evolve. From this perspective, the challenge is no longer only to evaluate models, but to understand and govern agent behaviour, interactions, and decision environments. As organizations begin to deploy AI agents within workflows, platforms, and information infrastructures, questions of transparency, accountability, and coordination become central. The talk argues that computational social science—and particularly traditions such as agent-based modelling—offers valuable conceptual tools for analysing this emerging landscape. Concepts such as interaction rules, bounded rationality, emergence, and multi-agent dynamics may become essential for understanding the behaviour of AI agents operating within complex social systems.

Speaker

Lecture Abstract

Artificial intelligence is undergoing a profound transformation. For much of its history, AI systems functioned primarily as analytical models: they classified images, predicted outcomes, or detected patterns in data. Today, however, a new generation of systems is emerging. AI agents built on large language models can plan tasks, access tools, interact with data environments, and coordinate actions across digital systems.

In this shift, AI is moving from model to actor.

This transformation has far-reaching implications. As AI systems begin to act autonomously in digital infrastructures—interacting with humans, organizations, and other agents—they become embedded in complex social systems rather than merely analysing them.

Recent developments in AI agent architectures illustrate this transition. By combining large language models with memory, planning mechanisms, and tool access, AI agents are able to pursue goals, interact with data sources, and execute sequences of actions across digital environments. These capabilities blur the traditional boundary between analytical models and operational decision systems.

Rather than viewing AI purely as a technological capability, we may need to understand it as a new class of actors embedded in socio-technical systems. This perspective opens a new research frontier for computational social science: studying and shaping societies in which human and artificial agents increasingly interact, collaborate, and co-evolve.

From this perspective, the challenge is no longer only to evaluate models, but to understand and govern agent behaviour, interactions, and decision environments. As organizations begin to deploy AI agents within workflows, platforms, and information infrastructures, questions of transparency, accountability, and coordination become central.

The talk argues that computational social science—and particularly traditions such as agent-based modelling—offers valuable conceptual tools for analysing this emerging landscape. Concepts such as interaction rules, bounded rationality, emergence, and multi-agent dynamics may become essential for understanding the behaviour of AI agents operating within complex social systems.

Professor Kayla de la Haye, University of California, Los Angeles (UCLA) Fielding School of Public Health

Lecture Title - Community-Engaged Systems Science for Public Health: Insights from Food and Nutrition Research

Speaker	Lecture Abstract
	Community-engaged systems science offers powerful tools for tackling complex public health problems — particularly when co-produced with the communities and stakeholders who are both actors in, and impacted by, the system. This talk illustrates this approach through two examples. First, a partnership with Los Angeles County government to build smart tools and analytics for community food systems, using participatory group model building and systems modeling to address food insecurity and guide local food policy. Second is the development of systems and agent-based models within a large precision nutrition consortium, to map ecological factors across individual, household, community, and structural levels shaping equitable uptake of personalized nutrition, and identify leverage points for population-level interventions.

Speaker

Lecture Abstract

Community-engaged systems science offers powerful tools for tackling complex public health problems — particularly when co-produced with the communities and stakeholders who are both actors in, and impacted by, the system. This talk illustrates this approach through two examples. First, a partnership with Los Angeles County government to build smart tools and analytics for community food systems, using participatory group model building and systems modeling to address food insecurity and guide local food policy. Second is the development of systems and agent-based models within a large precision nutrition consortium, to map ecological factors across individual, household, community, and structural levels shaping equitable uptake of personalized nutrition, and identify leverage points for population-level interventions.