/  Preliminary programme
MondayTuesdayWednesday
09.00 - 10.00
Welcome coffee
09.00 - 09.20

Gian-Marco Rignanese
UC Louvain
09.20 - 10.00
Welcome coffee
09.00 - 09.20

Olle Sandin
Swerim
09.20 - 09.40
Cross-process optimization in steel plate production through digital twin technology and distributed machine learning

Robert David
Technord, ArcelorMittal
09.40 - 10.00
Cowpers modelling and new driving paradigm
10.00 - 11.00
Ge Lei
Imperial College London
10.00 - 10.40

Coffee break
10.40 - 11.00
Charles Snyers
VUB
10.00 - 10.20
Development of a model-free reinforcement learning-based MIMO controller for directed energy deposition using a simulation-based framework

Héléna Verbeeck
UGent
10.20 - 10.40
Toward reliable slag property prediction: from classical molecular dynamics to machine-learning force fields

Coffee break
10.40 - 11.00
11.00 - 12.00
Sergio Martin-del-Campo
Viking Analytics
11.00 - 11.20
Automatic fault detection in metal manufacturing via wireless vibration monitoring using behavior-based analytics

Melvin Zinngrebe
Aurubis AG
11.20 - 11.40
From pixels to PLC: Architecting safe computer vision at the industrial edge

Jan Franssens
Apixa NV
11.40 - 12.00
Learning normality: Anomaly detection as a scalable strategy for metallurgical surface inspection
Els Nagels
InsPyro
11.00 - 11.20
Use of a digital twin to develop and optimize a H based alternative for Waetz kiln operations (Dust2Value project)

Daniel Bartz
Aurubis AG
11.20 - 11.40
Active learning for slag classification: from composition to environmental compliance

Manuel Michiels
Umicore
11.40 - 12.00
AI-driven source attribution of fine dust emissions in precious metals recycling
12.00 - 13.00
Gaétan Symens
CRM Group
12.00 - 12.20
Zinc coating monitoring at hot dip galvanising

Lunch
12.20 - 13.40
Akhilesh Swarnakar
ESTEP
12.00 - 12.20
Digitalisation as a decarbonisation accelerator: ESTEP's Integrated Approach to Sustainable Steel Production

Lunch
12.20 - 13.20
13.00 - 14.00
Welcome coffee
13.00 - 14.00
14.00 - 15.00
Prof. Valentina Colla
Pisa University
14.00 - 14.40
TBC

Dr. Menno Van der Winden
Umicore
14.40 - 15.20
TBC

Coffee break
15.20 - 15.40

Robrecht Verhelle
Bekaert
15.40 - 16.00
A robust method for multi sensor alignment applied during hot dip galvanizing
David Waroquiers
Matgenix
14.00 - 14.20
Accelerating alloy and coating development using AI: a case study combining active learning and atomistic simulation

Pengru Zhao
Université de Lorraine, CNRS, Université de Montpellier
14.20 - 14.40
Deep learning-based grain boundary segmentation in backscattered electron images

Antoine Hilhorst
UCLouvain, WEL Research Institute
14.40 - 15.00
From data to discovery of TWIP alloys by linking stacking energies, compsition, and mechanical properties
15.00 - 16.00
Jasper Somers
Aluminium Duffel BV
15.00 - 15.20
Integrating AI image analysis into fillform corrosion assessment of aluminium body sheet

Coffee break
15.20 - 15.40

prof. Pascal Jacques
UCLouvain
15.40 - 16.00
Machine learning approach for the development of new I²-metastable Ti alloys best-suited for additive manufacturing
16.00 - 17.00
Jeroen Van Wittenberghe
OCAS - ArcelorMittal
16.00 - 16.20
On digital twins and fatigue crack sensors: How industrial IoT Tehcnology can increase the reliability of cranes in the steel industry

Michael Sluydts
ePotentia
16.20 - 16.40
Can we trust generative AI for materials science?

Tim De Grave
ArcelorMittal
16.40 - 17.00
Improving maintenance in steel plants: Expert capture and enterprise date processing for MTTR reduction
Michael Sluydts
ePotentia, UGent
16.00 - 16.20
Predicting real properties with fake data: How GenAI can help complete materials dataset

Alexis Miroux
Aluminium Duffel BV
16.20 - 16.40
Predicting the properties of aluminium rolled products from full-scale production data

Thierry Decocq
YQ Purchasing
16.40 - 17.00
AI prompt engineering for metallurgy supply chains
17.00 - 18.00
18.00 - 19.00
Conference dinner
18.00 - 21.00
19.00 - 20.00
20.00 - 21.00

Monday

Tuesday

Wednesday

MondayTuesdayWednesday
09.00 - 10.00
Welcome coffee
09.00 - 09.20
Welcome coffee
09.00 - 09.20
10.00 - 11.00
Coffee break
10.40 - 11.00
Coffee break
10.40 - 11.00
11.00 - 12.00
12.00 - 13.00
Lunch
12.20 - 13.40
Lunch
12.20 - 13.20
13.00 - 14.00
Welcome coffee
13.00 - 14.00
14.00 - 15.00
15.00 - 16.00
Coffee break
15.20 - 15.40
Coffee break
15.20 - 15.40
16.00 - 17.00
17.00 - 18.00
18.00 - 19.00
Conference dinner
18.00 - 21.00
19.00 - 20.00
20.00 - 21.00

Monday

  • Welcome coffee
    13.00 - 14.00
  • Coffee break
    15.20 - 15.40

Tuesday

  • Welcome coffee
    09.00 - 09.20
  • Coffee break
    10.40 - 11.00
  • Lunch
    12.20 - 13.40
  • Coffee break
    15.20 - 15.40
  • Conference dinner
    18.00 - 21.00

Wednesday

  • Welcome coffee
    09.00 - 09.20
  • Coffee break
    10.40 - 11.00
  • Lunch
    12.20 - 13.20
MondayTuesdayWednesday
10.00 - 11.00
Coffee break
10.40 - 11.00
Coffee break
10.40 - 11.00
11.00 - 12.00
12.00 - 13.00
13.00 - 14.00
14.00 - 15.00
15.00 - 16.00
Coffee break
15.20 - 15.40
Coffee break
15.20 - 15.40

Monday

  • Coffee break
    15.20 - 15.40

Tuesday

  • Coffee break
    10.40 - 11.00
  • Coffee break
    15.20 - 15.40

Wednesday

  • Coffee break
    10.40 - 11.00
MondayTuesdayWednesday
18.00 - 19.00
Conference dinner
18.00 - 21.00
19.00 - 20.00
20.00 - 21.00

Tuesday

  • Conference dinner
    18.00 - 21.00
MondayTuesdayWednesday
09.00 - 10.00
Olle Sandin
Swerim
09.20 - 09.40
Cross-process optimization in steel plate production through digital twin technology and distributed machine learning

Robert David
Technord, ArcelorMittal
09.40 - 10.00
Cowpers modelling and new driving paradigm
10.00 - 11.00
Charles Snyers
VUB
10.00 - 10.20
Development of a model-free reinforcement learning-based MIMO controller for directed energy deposition using a simulation-based framework

Héléna Verbeeck
UGent
10.20 - 10.40
Toward reliable slag property prediction: from classical molecular dynamics to machine-learning force fields
11.00 - 12.00
Sergio Martin-del-Campo
Viking Analytics
11.00 - 11.20
Automatic fault detection in metal manufacturing via wireless vibration monitoring using behavior-based analytics

Melvin Zinngrebe
Aurubis AG
11.20 - 11.40
From pixels to PLC: Architecting safe computer vision at the industrial edge

Jan Franssens
Apixa NV
11.40 - 12.00
Learning normality: Anomaly detection as a scalable strategy for metallurgical surface inspection
Els Nagels
InsPyro
11.00 - 11.20
Use of a digital twin to develop and optimize a H based alternative for Waetz kiln operations (Dust2Value project)

Daniel Bartz
Aurubis AG
11.20 - 11.40
Active learning for slag classification: from composition to environmental compliance

Manuel Michiels
Umicore
11.40 - 12.00
AI-driven source attribution of fine dust emissions in precious metals recycling
12.00 - 13.00
Gaétan Symens
CRM Group
12.00 - 12.20
Zinc coating monitoring at hot dip galvanising
Akhilesh Swarnakar
ESTEP
12.00 - 12.20
Digitalisation as a decarbonisation accelerator: ESTEP's Integrated Approach to Sustainable Steel Production
13.00 - 14.00
14.00 - 15.00
David Waroquiers
Matgenix
14.00 - 14.20
Accelerating alloy and coating development using AI: a case study combining active learning and atomistic simulation

Pengru Zhao
Université de Lorraine, CNRS, Université de Montpellier
14.20 - 14.40
Deep learning-based grain boundary segmentation in backscattered electron images

Antoine Hilhorst
UCLouvain, WEL Research Institute
14.40 - 15.00
From data to discovery of TWIP alloys by linking stacking energies, compsition, and mechanical properties
15.00 - 16.00
Robrecht Verhelle
Bekaert
15.40 - 16.00
A robust method for multi sensor alignment applied during hot dip galvanizing
Jasper Somers
Aluminium Duffel BV
15.00 - 15.20
Integrating AI image analysis into fillform corrosion assessment of aluminium body sheet

prof. Pascal Jacques
UCLouvain
15.40 - 16.00
Machine learning approach for the development of new I²-metastable Ti alloys best-suited for additive manufacturing
16.00 - 17.00
Jeroen Van Wittenberghe
OCAS - ArcelorMittal
16.00 - 16.20
On digital twins and fatigue crack sensors: How industrial IoT Tehcnology can increase the reliability of cranes in the steel industry

Michael Sluydts
ePotentia
16.20 - 16.40
Can we trust generative AI for materials science?

Tim De Grave
ArcelorMittal
16.40 - 17.00
Improving maintenance in steel plants: Expert capture and enterprise date processing for MTTR reduction
Michael Sluydts
ePotentia, UGent
16.00 - 16.20
Predicting real properties with fake data: How GenAI can help complete materials dataset

Alexis Miroux
Aluminium Duffel BV
16.20 - 16.40
Predicting the properties of aluminium rolled products from full-scale production data

Thierry Decocq
YQ Purchasing
16.40 - 17.00
AI prompt engineering for metallurgy supply chains

Monday

Tuesday

Wednesday

MondayTuesdayWednesday
09.00 - 10.00
Gian-Marco Rignanese
UC Louvain
09.20 - 10.00
10.00 - 11.00
Ge Lei
Imperial College London
10.00 - 10.40
11.00 - 12.00
12.00 - 13.00
13.00 - 14.00
14.00 - 15.00
Prof. Valentina Colla
Pisa University
14.00 - 14.40
TBC

Dr. Menno Van der Winden
Umicore
14.40 - 15.20
TBC
15.00 - 16.00

Monday

Tuesday

MondayTuesdayWednesday
12.00 - 13.00
Lunch
12.20 - 13.40
Lunch
12.20 - 13.20
13.00 - 14.00

Tuesday

  • Lunch
    12.20 - 13.40

Wednesday

  • Lunch
    12.20 - 13.20
MondayTuesdayWednesday
09.00 - 10.00
Welcome coffee
09.00 - 09.20
Welcome coffee
09.00 - 09.20
10.00 - 11.00
11.00 - 12.00
12.00 - 13.00
13.00 - 14.00
Welcome coffee
13.00 - 14.00

Monday

  • Welcome coffee
    13.00 - 14.00

Tuesday

  • Welcome coffee
    09.00 - 09.20

Wednesday

  • Welcome coffee
    09.00 - 09.20
No events available!