Industrial Machine Learning in Action: From Models to Operations
Industrial ML in Action—From scientific ML to predictive maintenance, discover how data scientists and engineers turn models into measurable impact across operations, with cases from both academia and the industry.
Industrial Machine Learning in Action: From Models to Operations
Where algorithms meet the factory floor.
Join us for a half-day deep dive into how machine learning moves from concept to real-world impact in industrial settings. You'll get hands-on insights, proven frameworks, and case studies covering best-practice MLOps and energy and process optimization.
Between talks, there’s plenty of time to connect with other professionals—engineers, data folks, and operations teams—who are tackling similar challenges and exploring new ideas.
Preliminary Program:
09.00 - 09.30 Registration coffee and crossaint
09.30 - 09.45 Welcome and introduction of the day
09.45 - 10.15 Professor Allan Engsig-Karup, DTU Compute - "Scientific Machine Learning"
10.15 - 10.45 PhD fellow Søren Villumsen, DTU Department for Chemical and Biochemical Engineering, - "Real-time machine learning for industrial chemical process optimization: learnings from 5 case studies"
10.45 - 11.05 Break
11.05 - 11.35 Thor Steen Larsen, ML Engineer | MLflow ambassador, DSB (TBA)
11.35 - 12.05 Rasmus Steiniche, Ceo Neurospace - The MLOps Trifecta in action: Scalability, Traceability and Efficiency
12.05 - 12.35 Manager and Lead Data Scientist Francesc Joan Riera, Danish Crown - Innovate from the ground-up: framework and case examples”
12.35 - 13.30 Network lunch (sandwich)
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