Christian Andersson Naesseth

Christian Andersson Naesseth is an Assistant Professor of Machine Learning at the University of Amsterdam, affiliated with the Informatics Institute, the Amsterdam Machine Learning Lab (AMLab), and the UvA-Bosch Delta Lab 2. A former postdoctoral researcher at Columbia University and PhD graduate in Electrical Engineering from Linköping University (advised by Fredrik Lindsten and Thomas Schön), his research bridges generative modeling, uncertainty quantification, and approximate Bayesian inference with applications in AI for Science.

Research Interests

• Generative Models (diffusions, flows, flow networks)
• Approximate Inference (variational and Monte Carlo methods)
• Probabilistic Modeling (natural sciences, computer vision, health)
• Uncertainty Quantification (E-values, conformal prediction)

Recent Scientific Contributions

• Developed SDE Matching for simulation-free training of latent stochastic differential equations
• Advanced controlled generation via equivariant variational flow matching
• Proposed risk monitoring frameworks for test-time adaptation under unknown data shifts

Awards & Recognition

• Best Workshop Paper Award at AABI 2025

Advising & Collaborations

• Lab manager of UvA-Bosch Delta Lab 2
• Collaborates with institutions like Mila Montreal, Microsoft Research, and ECMWF
• Mentors students: Grigory Bartosh (PhD), Hany Abdulsamad (postdoc), and visiting PhDs from Antwerp, Manchester, Bielefeld, and DTU