Scientific interests - links to project pages and papers can be found below:
- Machine learning. Novel methods for solving difficult inference problems.
- Approximate Bayesian inference with deterministic methods. Manfred Opper and I have contributed to the development of Expectation Propagation (formerly known as Adaptive TAP and also called Expectation Consistent by us). Current interests are perturbation corrections to EP with Ulrich Paquet and Manfred Opper and linear response and cavity methods for improving the Laplace approximation with Aki Vehtari and Aki's group.
- Bioinformatics with specific focus on promoter analysis and gene regulation (see gene regulation group homepage), jointly headed by Anders Krogh, Albin Sandelin and me. We are interested in probabilistic modelling of genomic data such as gene expression micro-array type and sequence tags, chip-on-chip and CAGE in close collaboration with experimental groups at BRIC, the University hospital and Riken, Japan. My part of the group focus primarily on cancer research and use biological, machine learning and systems biology methods to address classification and survival.
- Approximate Bayesian inference with Markov chain Monte Carlo methods. I am interesting in MCMC for providing ground truth for deterministic methods and for making MCMC practical for large problems. This involves improving the mixing properties of Gibbs sampling type algorithms, proposal distributions for non-linear state space models and generalized ensemble methods to get marginal likelihood estimates.
- Some machine learning models that have been and still are very interesting: classification with Gaussian processes, independent component analysis (ICA), low rank matrix factorization for collaborative filtering, non-parametric Bayes, sparse linear latent variable models and non-linear state space models.
- Statistical Signal Processing. Inference algorithms for mobile communication and source separation in hearing instruments.
- Information retrieval in the medical domain.
- Probabilistic modeling in EEG.
Links to projects with separate pages
- Sparse Linear Identifiable Multivariate Modeling (SLIM)
- Propulsion modelling
- Ordinal matrix factorization (collaborative filtering)
- PASS-GP: Predictive Active Set Selection for Gaussian Processes
- FindZebra: a Vertical Search Engine for Rare Diseases
- HemaExplorer - see the expression of your favourite gene in the hematopoietic system
Old short CV, Old long CV, semi-old research profile in English and semi-old research profile in Danish.
Download preprint and papers from ORBIT, the DTU research database.
Old preprints and papers page still available but not updated regularly.
Download old software.
Current students (main supervisor unless otherwise stated):
- Trine Julie Abrahamsen (DTU, co-supervisor)
- Frederik Otzen Bagger (KU)
- Ditte Høvenhoff Hald (DTU)
- Tomas Martin-Bertelsen (KU)
- Konrad Stanak (DTU)
- Morten Nonboe Andersen (DTU)
- Thomas Beierholm (DTU)
- Morten Hansen (DTU)
- Ricardo Henao (DTU and KU)
- Jens Vilstrup Johansen (KU)
- Bogumil Kaczkowski (KU)
- Ulla Brasch Mogensen (KU, co-supervisor)
- Jóan Petur Petersen (DTU)
- Kare Brandt Petersen (DTU)
- Sune Olander Rasmussen (KU, co-supervisor)
- Carsten Stahlhut (DTU, co-supervisor)
- Man-Hung Eric Tang (KU, joint supervision with Albin Sandelin and Anders Krogh)
- Eivind Valen (KU, joint supervision with Albin Sandelin and Anders Krogh)
- Nicolas Rapin (KU)
Master projects are available for DTU and KU students.