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Photo of Mr Mikkel Bue Lykkegaard

Mr Mikkel Bue Lykkegaard

Postgraduate Researcher (WISE CDT)


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Mikkel’s research is concerned with Bayesian inversion for hydrogeology – specifically using cutting-edge Markov Chain Monte Carlo (MCMC) techniques for groundwater flow parameter estimation and uncertainty quantification. He is particularly interested in the use of surrogate models in multi-level MCMC model hierarchies, and is currently exploring cutting-edge Machine Learning techniques for ultra-fast approximation of model response.

His work has applications in both groundwater abstraction and remediation – improved estimates of groundwater flow patterns can improve decision support systems, allowing groundwater abstraction companies to make better sustainable yield estimates, and remediation companies to design taylor-made remediation campaigns.  

Research Interests:

  • Environmental (geo-)hydrology and hydroinformatics
  • Uncertainty quantification and model sensitivity analysis
  • Distributed environmental models and surrogate models
  • Environmental fate and risk assessment of pollutants