PhD Defense | Santiago Ramos Garces | Enhanced Performance of Automatic Tuning in Isotope Separation Online Systems through Bayesian Optimization

Name: Santiago Ramos Garces

Research output: click here.

Date: December 1, 2025, 17h00 CET

Location:
Promotiezaal 
Klooster van de Grauwzusters
Stadscampus
Lange Sint-Annastraat 7
2000 Antwerpen
Livestream: click here.

SG

Enhanced Performance of Automatic Tuning in Isotope Separation Online Systems through Bayesian Optimization

Radioactive isotopes are essential for research in various scientific fields, including nuclear and atomic physics, as well as for applications in nuclear medicine. Their efficient extraction and transport represent a complex and challenging tuning task. This PhD research develops optimization algorithms to automate this process, making it faster, safer, and more reliable. The proposed automatic tuning framework reduces setup times from several hours to about 30 minutes and increases isotope yield by up to 87% compared to default settings, serving as an efficient supporting tool for manual tuning.

 

Promoter:

  • Stijn De Rammelaere (UANTWERPEN)

SCK CEN mentors:

  • Pedro João Fernandes Pinto Ramos
  • Marc Dierckx

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