Assessment of machine learning methods as a tool in detecting leakages

Kristian Gundersen

University of Bergen

Kristian Gundersen has a master in applied and computational mathematics from UiB from 2010. He started to work as a PhD on the BayMoDe project in January 2017. The aim of the project is to develop new methods for detection of CO2- leakages using a Bayesian approach and machine learning techniques. Kristian has also five years experience as a Safety engineer at Safetec Nordic.  


  1. Kristian Gundersen (University of Bergen)
  2. Guttorm Alendal (University of Bergen)
  3. Hans Skaug (University of Bergen)
  4. Helge Avlesen (University of Bergen)
  5. Jerry Blackford (Plymouth Marine Laboratory)
  6. Baixin Chen (Heriot-Watt University)
  7. Marius Dewar (Heriot-Watt University)
  8. Jarle Berntsen (UIB)

Topic Areas

Other , EU project SUCCESS


Poster » Poster session (15:20 - Tuesday, 13th June)