Digitalization and AI for Energy Efficiency

Welcome to our third webinar in the Industrial Transition Series!

 Time:             21 January 2026, 15:00 – 17:00 CET

Place:            Online

Moderator:   Heikke Brugger, IREES GmbH

Registration: https://events.teams.microsoft.com/event/9cceea4b-d9eb-437d-9b15-84ae6609836d@fd44d5d4-bbac-4ce4-b734-c9f595398cad

Link to the invitation in pdf format

Preliminary PROGRAMME

Introduction to the IETS TCP
Elin Svensson, IETS Secretariat

Introduction to IETS Task XVIII on Digitalization, Artificial Intelligence and Related Technologies for Energy Efficiency and GHG Emissions Reduction in Industry
Mouloud Amazouz, Task Manager, CanmetENERGY, Natural Resources Canada

Project presentations:

• Foundation Models in the Energy Sector: Integration Potential and Challenges
  Mehrzad Lavassani, RISE Research Institutes of Sweden
  Foundation Models (FMs) is a new class of Artificial Intelligence that learns general-purpose representations that create unique opportunities in various energy use cases and applications. This presentation provides an overview of a recent study on the assessment of FMs.
• KI4ETA
  Heiko Ranzau, Etalytics, Germany
  The goal of the KI4ETA project is to develop tools that help energy managers and consultancies close the energy efficiency gap in industry.
• Towards Autonomous Industrial Operations: Causal and Multi-Agent RL for Supervisory Control of Energy-Intensive Processes
  Karim Nadim and Ahmed Ragab, CanmetENERGY, Natural Resources Canada
  Contents to be announced.
• DECODE – Data-driven best practice for energy-efficient operation of industrial processes
  Zhipeng Michael Ma, PhD, Postdoctoral Researcher, SDU Center for Energy Informatics, University of Southern Denmark
  DECODE develops data-driven methods and digital tools to optimize industrial process operation, improving energy efficiency and reducing CO₂ emissions through advanced analytics, modelling, and decision support.

Q&A, discussion