I am currently a postdoctoral researcher at the University of Eastern Finland as part of the inverse problems research group. I currently work on inverse problems in functional and quantitative MRI.

Research Interests:

My general research interests lie in using techniques from mathematical optimization, numerical mathematics and probability theory/statistics in inverse problems, image processing and machine learning. In particular, the theory and application of regularization strategies and prior modeling.

Particular research includes:

• Constrained and sparsity-promoting inference:
  • monotonic Gaussian processes
  • projected distributions
  • regularized Gaussians
• Prior modeling strategies:
  • implicit priors
  • one-bit compressed sensing with generative models
• Imaging applications:
  • EIT with partial data
  • fast-ion tomography
• Non-Bayesian uncertainty quantification methodologies:
  • self-supervised conformal prediction

Previous positions:

Until September 2025, I was a postdoctoral researcher at the Technical University of Denmark as part of the CUQI research project on Computational Uncertainty Quantification for Inverse Problems. I worked on the use of tools from mathematical optimization for modeling and sampling in Bayesian inverse problems.