Measuring and Forecasting Complex Economic Systems

Join us in person for an exciting event diving into the world of how complex economic systems can be measured and forecast using engineering approaches, data integration, and machine learning. Bringing together perspectives from economics, data science, and energy systems, this event offers a unique opportunity to learn, discuss, and connect across disciplines.

Hybrid event: attend in person or online.
? In-person: Warwick Campus
? Online: Microsoft Teams (link sent after registration)

Overview

This cross‑disciplinary workshop brings together researchers and practitioners from economic measurement, machine learning, and energy systems modelling. As economies become increasingly digital, interconnected, and data‑rich, traditional measurement and forecasting frameworks are under pressure to evolve.

This event explores how new data sources, advanced analytical methods, and domain‑specific modelling can help us better capture complexity, understand dynamic systems, and support policy‑relevant insights.

Info: Setting the context: the need for integrated approaches to understanding complex systems.

Info: Exploring how digitalization reshapes production, consumption, and statistical measurement frameworks.

Info: How modern machine learning and multimodal data integration can enhance modelling and forecasting.

Info: A deep dive into energy systems modelling as a complex, data intensive domain with cross sector impacts.

Info: Interactive discussion with all speakers on cross cutting opportunities and methodological innovation.

Info: An opportunity to connect, collaborate, and explore future research directions.

Know what’s Happening Next — before everyone else does.

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Host or Publisher School of Engineering, The University of Warwick