A tough choice for the evaluation committee

In order to identify the best AI master’s theses in 2021, we reached out to the research community at NTNU to nominate excellent theses within AI. This resulted in the list of nominations that you can see to the right. The evaluation committee was made up by NAIL researchers and representatives from partners DNB and Telenor. Their job was to select the top three out of the 13 nominees, which was not an easy task, as the overall quality was very high. 

The nominations covered a variety of topics, both within applied and theoretical AI. This year’s nominees were also a more diverse group of candidates than earlier. For instance, there were many more female students nominated to the awards than previous years. We’re happy to see this, as AI is still a male-dominated field. In addition, the nominees had different academic backgrounds and represented five different departments. In the end, the committee managed to boil it down to these three:

• Anna Haugsbø Hermansen - Machine Learning for Spatio-Temporal Forecasting of Ambulance Demand: a Norwegian Case Study (Dept of Computer Science)
• Sindre Stenen Blakseth - Introducing CoSTA: A Deep Neural Network Enabled Approach to Improving Physics-Based Numerical Simulations (Department of Physics)
• Anna Rodum Bjøru - The importance of disentanglement when learning representations (Dept of Computer Science)

The awards ceremony

Anna, Sindre and Anna were invited to present their work during the awards event that took place at Gløshaugen. Before the nominees presented their work, Massimiliano Ruocco, research scientist at SINTEF and adjunct associate professor at NTNU, gave a talk on his experience working with companies and academia on industrial master’s theses. We also heard from the two student organisations, BRAIN and Cogito, who presented their activities and plans for 2022.