About me

I am a computational social scientist and Research Fellow at Trinity College Dublin, based at the Centre for Sociology of Humans and Machines (SOHAM). I study collective dynamics in social systems, with a focus on how algorithms and AI shape attention, belief, knowledge, and social interaction.

My research began with questions about collective attention and online information dynamics. During my PhD in Network Science at Central European University, I investigated how ranking algorithms and platform interventions shape public attention on social media. Building on this foundation, my postdoctoral research at University College Dublin and Trinity has expanded to human–AI social systems. I study how AI agents influence collective beliefs, how people respond to AI in positions of authority, and how AI-generated knowledge differs from human-produced knowledge.

I combine large-scale digital trace data, behavioural experiments, agent-based modelling, and network science to investigate these questions. I am also the lead author of a review on AI-enhanced collective intelligence published in Patterns, which proposes a multilayer framework for understanding how collective intelligence emerges from interactions between humans and AI agents.

My work has been featured in The Conversation, de Volkskrant, MIT Technology Review (Chinese edition), and LSE Impact.

“The real danger is not that computers will begin to think like humans, but that humans will begin to think like computers.”

— Sydney J. Harris

Research

Switch between the themes I study and the roles machines play, click a column to see the projects behind it, and click a project to see how it fits.

Collective dynamics in human–machine social systems How attention, belief, and knowledge emerge and evolve as algorithms and AI enter social life
Conceptual framework
AI-enhanced collective intelligence (Patterns, 2024)  ·  Behavioural sociology of humans and machines (Springer Handbook of Hybrid Intelligence, accepted)
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Two of my papers approach hybrid intelligence from complementary directions. AI-enhanced collective intelligence (Patterns, 2024) proposes a multilayer representation of human–AI collective intelligence, with cognition, physical, and information layers, and examines how diversity and network structure shape collective outcomes. Behavioural sociology of humans and machines (Springer Handbook of Hybrid Intelligence, accepted) turns to the social mechanisms operating within such systems, tracing how people categorise AI, how reciprocity and authority change when machines participate, and how these patterns become embedded in organisations.
Framework figure linking AI-enhanced collective intelligence and behavioural sociology of humans and machines to hybrid intelligence

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Selected publications

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Media & gallery

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