Mathematical Sciences
University of Gothenburg/
Chalmers
Vice-Dean for Research and Research Infrastructures
Faculty of Science, University of Gothenburg
Start date TBA.
This position is funded through the Knut and Alice Wallenberg Foundation.
Project: "The Routes of Glioblastoma and their Patient-Specific Vulnerabilities"
Link to the application system TBA.
• Recent papers and presentations
Vincent Szolnoky recently presented our paper On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity at NeurIPS 2022.
Oskar Allerbo recently presented our paper Bandwidth Selection for Gaussian Kernel Ridge Regression via Jacobian Control at ICSDS2022 . My research centers on the development of new statistical methodology for neural networks, network modeling, clustering and model selection, with applications to high-dimensional biological data.
My group consists of 3 PhD students and 3 postdocs. We work on projects ranging from multi-group and multi-view data integration, multilayer network modeling, interpretable deep neural networks and analysis challenges in systems biology. For more details, please check the List of Current Projects below - we are always looking for master students who want to get involved in research projects.
Data integration and joint modeling are a rich source for research problems. These types of problems are central components in
several joint projects in collaboration with Sven Nelander's group.
Our group aims to formulate integrated models for mRNA, microRNA, DNA copy number, methylation and mutation in human cancer. These projects are supported
by two grants from the Swedish Foundation for Strategic Research as well as the Wallenberg AI, Autonomous Systems and Software
Program (WASP)
and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS).
We also collaborate with Mika Gustafsson's group at
Linköping university on data integration tasks, with a special emphasis on the utilization of prior biological information. This project is also funded through WASP and DDLS.
I collaborate with Johan Jonasson on new regularization techniques for deep neural networks to better handle the presence of mislabeled data. This project is supported by the Wallenberg foundation
In a joint research project with Professor Giuseppe Durisi , Chalmers Electrical Engineering, we investigate the generalization properties of deep neural networks - how come such over-parameterized models perform so well on test data? The project "Generalization bounds for Deep Neural Networks: Insight and Design" is funded through the WASP Graduate School .
Together with Balazs Kulcsar at Electrical Engineering, we work on research problems merging control theory and neural networks. Centiro, have funded two industry PhD positions on this topic.
Since 2018, I am the Vice-Dean for Research and Research Infrastructures at Faculty of Science , University of Gothenburg. I chair the Faculty Board's advisory committee, where we discuss interdepartmental activities, review sabbatical applications and Faculty prizes and awards. We also organize faculty events.
In past years I have cycled teaching applied statistics couses (Linear models, Applied multivariate analysis) and method courses (Statistical inference principles and Survival analysis).
My main focus for teaching now is Statistical Learning for Big Data and master thesis projects.
Here are some links to recent courses:
