Teaching

Current courses

IN3050/4050 - Introduction to Artificial Intelligence and Machine Learning (Coordinator and lecturer), University of Oslo (Spring 2020 - )

IN5490/9490 - Advanced Topics in Artificial Intelligence for Intelligent Systems (Coordinator, project co-advisor and co-lecturer), University of Oslo (Autumn 2019 - )

Past courses

INF3490/4490 - Biologically inspired computing (Lecturer and co-coordinator), University of Oslo (2016 - 2018)

TDT4171 - Artificial Intelligence Methods (Teaching assistant), Norwegian University of Science and Technology (2014)

TDT4265 - Computer Vision (Teaching assistant), Norwegian University of Science and Technology (2011, 2012, 2013)

IT3105 - Artificial Intelligence Programming (Teaching assistant and coordinator), Norwegian University of Science and Technology (2011, 2012)

TDT4105 - Informasjonsteknologi Grunnkurs (Teaching assistant and substitute lecturer), Norwegian University of Science and Technology (2010)

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Supervision

Ongoing

PhD-Students

Ivar-Kristian Waarum, main supervisor, University of Oslo. 2022-

Mateusz Wasiluk, main supervisor, University of Oslo. 2022-

Shin Watanabe, main supervisor, University of Oslo. 2022-

Mia-Katrin Ose Kvalsund, co-supervisor, University of Oslo. 2022-

Katrine Linnea Nergård, co-supervisor, University of Oslo. 2021-

Emma Stensby Norstein, co-supervisor, University of Oslo. 2020-

Master Students

I'm having the pleasure of supervising so many master students that I'm not quite able to keep this section up-to-date

Completed

PhD-Students

Bjørn Ivar Teigen, PhD co-supervisor, University of Oslo: Opportunities and Limitations in Network Quality Optimization; Quality Attenuation Models of WiFi Network Variability 2019-2022

Jørgen Halvorsen Nordmoen, PhD co-supervisor, University of Oslo: Enhancing MAP-Elites to overcome challenges in Evolutionary Robotics. 2016-2021

Master-Students

Tommy Phan: Exploring the Potential of Hierarchical Quality-Diversity Algorithms for Robot Navigation (2022)

Kristian Roa Gran: Learning to drive by predicting the future (2022)

Eirik Solheim Ølberg: CHILD: Predicting simulation outcome in open-ended co-evolution (2022)

David Andreas Bordvik: Forecasting regulation market balancing volumes from market data and weather data using Deep Learning and Transfer Learning (2022)

Vegard Bjørsvik: Solving Sparse Reward Environments Using Go-Explore with Learned Cell Representation. (2021)

Sindre Thorsesen: Solving Long Term Planning Problems with Direct Future Prediction. (2021)

Patrick Ribu Gorton: Backpropagating to the Future: Evaluating Predictive
Deep Learning Models. (2020)

Scott Andreas Sørensen: Comparing Model-Free and Model-Based Reinforcement Learning for Collision Avoidance. (2020)

Bjørn Ivar Teigen, University of Oslo: An active learning perspective on exploration in reinforcement learning. (2018)

Jorunn Helene Melby, Master co-supervisor, NTNU: A Framework for Evolution of Behaviour Switching (2013)

Kim Verner Soldal, Master co-supervisor, NTNU: Modularity as a Solution to Spatial Interference in Neural Networks (2012)