Tuesday 29th september

TimingSpeakerCategory
09:00Welcome coffee
09:20Keynote Speaker

Gian-Marco Rignanese
UC Louvain
From high-throughput ab initio calculations to machine learning: the new era of materials informatics
10:00Keynote Speaker

Ge Lei
Imperial College London
From trust to action: large language models for scientific discovery and decision support
10:40Coffee break
11:00Sergio Martin-del-Campo
Viking Analytics
Automatic fault detection in metal manufacturing via wireless vibration monitoring using behaviour-based analytics		Quality Assurance & Safety
11:20Daniel Bartz
Aurubis AG
From pixels to PLC: architecting safe computer vision at the industrial edge		Quality Assurance & Safety
11:40Jan Fransens
Apixa NV
Learning normality: anomaly detection as a scalable strategy for metallurgical surface inspection		Quality Assurance & Safety
12:00Gaétan Symens
CRM Group
Zinc coating monitoring at hot dip galvanising		Quality Assurance & Safety
12:20Lunch
13:40Thierry Decocq
YQ Purchasing
AI Prompt Engineering for Metallurgy Supply Chains		Supply Chain Optimization
14:00David Waroquiers
Matgenix
Accelerating alloy and coating development using AI: A case study combining active learning and atomistic simulations		Alloy Development & Material Innovation
14:20Pengru Zhao
Université de Lorraine, CNRS, Université de Montpellier
Deep learning-based grain boundary segmentation in backscattered electron images		Alloy Development & Material Innovation
14:40Antoine Hilhorst
UCLouvain, WEL Research Institute
From data to discovery of TWIP alloys by linking stacking energies, composition, and mechanical properties		Alloy Development & Material Innovation
15:00Jasper Somers
Aluminium Duffel BV
Integrating AI image analysis into filiform corrosion assessment of aluminium body sheet		Alloy Development & Material Innovation
15:20Coffee break
15:40Pascal Jacques
UCLouvain
Machine learning approach for the development of new β-metastable Ti alloys best-suited for additive manufacturing		Alloy Development & Material Innovation
16:00Michael Sluydts
ePotentia, UGent
Predicting real properties with fake data: how GenAI can help complete materials datasets		Alloy Development & Material Innovation
16:20Alexis Miroux
Aluminium Duffel BV
Predicting the properties of aluminium rolled products from full‑scale production data		Alloy Development & Material Innovation
16:40Nicolas Dubois
Nyrstar
Harnessing data science for zinc industry cellhouse – building a model that quantifies the impact of influencing factors on the current efficiency		Supply Chain Optimization
18:30Conference dinner