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Innovations in Data Synthesis: a SPRITE+ innovation forum

  • spriteplus
  • 21 hours ago
  • 1 min read
“Innovations in Data Synthesis” brought together field leaders and practitioners to explore the transformative potential of synthetic data in Manchester on 24th July 2025.
“Innovations in Data Synthesis” brought together field leaders and practitioners to explore the transformative potential of synthetic data in Manchester on 24th July 2025.

About the event

Synthetic data – from generative models to rule-based simulation – offers a methodology where privacy protection, data utility, and innovation intersect. This forum convened experts across disciplines to consider how emerging methods (like GANs, VAEs, diffusion models, and CART) are being applied in practice, especially in domains such as health, policing, social research, and finance. We critically examined trade-offs between utility, fidelity and risk, explored practical deployment strategies, and identified future needs for regulation, tooling, and standards.


Through focused discussion, we aimed to generate a position paper and set the agenda for a new community of practice at the intersection of data synthesis and TIPS (Trust Identity Privacy and Security).


Speaker slides

View the slides presented by several speakers who attended the Innovation Forum:


Using saturated count models for data synthesis - Robin Mitra:


A brief introduction to SynDiffix and the Anonymity Loss Coefficient - Paul Francis:


A paradigm for creating synthetic data with utility and privacy assessment - Gillian M Raab:


Agent-based models to generate synthetic data - Dr. J. Kasmire:


Two Worlds United? Synthetic Data in Computer Science and Statistics - Jörg Drechsler:


Synthetic Data – a data owner’s perspective - Iain Dove:


Applications of Evolutionary Data Synthesis - Mark Elliot:


Generating Private Databases with Markov Chain Monte Carlo - Harry Ros McArthur:


The Simulacrum: Enabling real-world patient studies with privacy preserving synthetic data - Lora Frayling:


Federated Synthetic Data Generation - Rudolf Mayer, SBA Research:


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