Job description

I am an Associate Professor in the Machine Learning Group at UiT. My research focuses on graph machine learning, covering both its theoretical foundations and applications to real-world problems. In particular, I study graph neural networks and their theoretical properties, including expressivity, stability, and transferability. I am also interested in learning on graphs with missing features and in developing graph-based methods for medical data and temporal networks.

Current Role

• Associate Professor in the Machine Learning Group.
• Member of the Northernmost Graph Machine Learning Group.
• Member of Visual Intelligence.
• Member of Integreat.

Research Interests

• Graph neural networks.
• Theoretical properties of graph neural networks, including expressivity, stability, and transferability.
• Machine learning on graphs with missing features.
• Graph neural networks for medical data.
• Temporal graph neural networks.

For more information, please visit my Google Scholar profile and my personal webpage. I am open to supervising students on a wide range of machine learning projects. Some project ideas are available on my personal webpage, but I am generally happy to discuss other topics that align with my research interests.