Kasper Bågmark

Postdoctoral researcher at Vrije Universiteit Amsterdam

Postdoctoral researcher at the Department of Mathematics, Vrije Universiteit Amsterdam.

Previously, I was a PhD student at the Division of Applied Mathematics and Statistics, Department of Mathematical Sciences, Chalmers University of Technology & University of Gothenburg, and within the research school of the Wallenberg AI, Autonomous Systems and Software Program (WASP).

Organization

  • Main organizer of DYNSTOCH 2026, a workshop on statistical methods for dynamical stochastic models, taking place in Gothenburg in June 2026
  • Co-organizer of the Statistics Seminar at the Department of Mathematical Sciences, Chalmers & University of Gothenburg

Education

  • Ph.D. Mathematics, Chalmers University of Technology & University of Gothenburg, 2023–2026. Thesis: “Learning to Estimate: Bayesian Filtering with Deep Density Methods”.
  • M.Sc. Engineering Mathematics and Computational Science, Chalmers University of Technology, 2018–2020. Thesis: “Approximation of non-stationary fractional Gaussian random fields”.
  • Exchange semester in Mathematics, ETH Zürich (Eidgenössische Technische Hochschule Zürich).
  • B.Sc. Mathematics, University of Gothenburg, 2015–2018.

Funding and Awards

  • Postdoctoral scholarship (WASP through Knut and Alice Wallenberg Foundation), 2026, 128,000 EUR. Project: “Uncertainty quantification for mathematical neuroscience with scientific machine learning”.
  • DYNSTOCH 2026 organizing grants from Wenner-Gren Foundations, Royal Swedish Academy of Sciences, and Wilhelm och Martina Lundgrens Vetenskapsfond, 2025, total 230,000 SEK
  • Best poster award at 29th Nordic Conference in Mathematical Statistics, 2023
  • Travel grants from Stiftelsen Längmanska kulturfonden, Kungl. Vetenskaps- och Vitterhets-Samhället (KVVS), and Stiftelsen för Vetenskaplig Forskning och Utbildning i Matematik (SveFUM), 2026