Trial lecture
Tuesday June 21, 2022, 10:15 am, in Kristen Nygaards sal (5370), Ole-Johan Dahls
Title: “Recent advances in explainable AI"
Main research findings
- Partial orders and directed acyclic graphs are common data structures that arise naturally in numerous applications, and that define order between data points. Examples are orders of
tasks in a project plan, transaction orders in distributed ledgers and execution sequences in computer programs, to mention a few.
On the other hand, hierarchical clustering is one of the oldest and most used methods for unsupervised classification and exploratory data analysis. In spite of this, few methods are rigged to take into account the information encoded in the order relation when performing hierarchical clustering of partially ordered data.
In his research, Daniel R. Bakkelund has developed new mathematical theory and algorithms to include this information in methods for hierarchical clustering, resulting in the concept
of "order preserving hierarchical clustering".
The efficacy of theories are demonstrated through experiments on real world data, and show that the in comparison with existing methods, the new methods excel both in cluster quality and
order preservation.
Adjudication committee:
- Associate Professor Nello Blaser, University of Bergen, Norway
- PD. Dr.-Ing. Anni-Yasmin Turhan, Dept. Of Computer Science, Dresden Technical University, Germany
- Associate Professor Nils Gruschka, University of Oslo, Department of informatics, Norway
Supervisors
- Associate Professor Henrik Forssell, Department of Informatics,UIO
- Professor Martin Giese, Department of Informatics, UiO
- Associate Professor Gudmund Hermansen, Department of Mathematics, UIO
Chair of defence:
Professor Carsten Griwodz
Candidate contact information: https://www.linkedin.com/in/daniel-bakkelund-b98532/
Contact information to Department: Mozhdeh Sheibani Harat