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.
Where algorithms meet the factory floor—and the lab.
Join us for a half-day deep dive into how machine learning transforms industrial operations, with a special focus on chemical and food engineering. Discover how Scientific Machine Learning (SciML) and robust MLOps practices—including model traceability, scalability, and experiment tracking—are driving innovation from research to production.
Through expert talks and real-world case studies, you'll gain practical insights into deploying ML in complex environments, optimizing energy and processes, and building resilient ML systems. Whether you're an engineer, data scientist, or operations lead, this event is your chance to connect with peers 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 in DSB, MLflow ambassador and DDSC Open-source Comittee Chair - "How to use MLflow for Experiment Tracking and Deployment and how we use it in DSB"
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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