PhD projects

I'm currently supervising the following PhD candidates:

• Samaneh Abolpour Mofrad, working on machine learning for medical data analysis.

MSc projects

Current MSc projects

Adrian Storm-Johannessen and Sondre Fossen-Romsaas (2018—2020). Generative adversarial networks and medical image synthesis.

Sivert Stavland (2018—2020). Topic: Machine learning and electronic health records.

Sindre Eik de Lange and Stian Heilund (2017—2019). Autonomous mobile therapeutic robot. Using advanced computer vision techniques (graph convolutional neural networks), and the Robot Operating System, the project aims at developing a robotic physical therapist for patient rehabilitation. Sindre wrote a short article on Medium about some of their work here: A Beginner’s Tale of A First Computer Vision Project.

Sathiesh Kumar Kaliyugarasan (2017—2019). Transfer learning in medical imaging. A study of how to best use transfer learning when training deep neural networks for biomedical image analysis. His work so far was presented at NVIDIA's GTC Europe in Münich, October 2018.

Feel free to contact me if you're interested in doing a MSc project in machine learning.

Completed MSc projects

• Sean Meling Murray (2017—2018). An Exploratory Analysis of Multi-Class Uncertainty Approximation in Bayesian Convolutional Neural Networks. Sean developing and explored new techniques for obtaining robust uncertainty estimates for deep neural networks. Thesis available: here. Went on to work at the Norwegian Computing Center: NR profile.

BSc projects

• Jon Einar Haraldsvik, Stian Gudvangen Gjerløw, Didrik Fanuelsen Tranvåg (2015). Tryg Maintenance App – A cross-platform application using Appcelerator Studio Cloud Services and Arrow DB. The students developed a cross-platform mobile application for Tryg Forsikring. The project was awarded "best bachelor project" at the department in 2016. The students went on to start Appivate AS.

Feel free to contact me if you're interested in doing a BSc project, preferably in machine learning.

Current courses

• DAT259 – Medical data analysis and deep learning, spring 2019.
• ELMED219, spring 2019. ELMED219 is an elective course on computational medicine at the University of Bergen medical school. A collaboration between the Department of Biomedicine, University of Bergen, Department of Computing, Mathematics and Physics, Western Norway University of Applied Sciences, and Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital. The course is offered to both medical students and engineering students and encourages collaborations between these disciplines, motivated by e.g. "The convergence revolution". Course website: ELMED219 @ MittUiB. Course code repository: https://github.com/MMIV-ML/ELMED219x
• MAT106 – Videregående matematikk for elektroingeniører, spring 2019.

I'm also involved in Health Care Informatics, a Continuing Education course at the University of Bergen. Topic: Artificial intelligence for natural language processing and speech recognition.

In addition to lecturing in these courses I'm creating supporting e-learning material: MAT106x, BMED360x, ELMED219x, NordBiomed, financed by the Erasmus+ KA2 strategic partnerships MedIm and HVL. To deliver these and other courses I've set up the e-learning platform AkademiX.

Past courses

• DAT158: Machine learning and advanced algorithms. Fall 2018. A practical, project-based, hands-on exploration of the fundamentals of machine learning, focusing on solving real-world problems. The course website is here: DAT158 Canvas site. The code used in the course is available in the course repo.
• DAT259 – Practical deep learning, spring 2018.
• MAT106 – Videregående matematikk for elektroingeniører, spring 2018.
• MAT100 – Grunnleggende matematikk for ingeniører, fall 2017, for students in the electrical engineering programs "Elkraftteknikk" and "Kommunikasjonssystemer"
• MAT106 – Videregående matematikk for elektroingeniører, spring 2016, for students in the electrical engineering programs "Elkraftteknikk" and "Kommunikasjonssystemer"
• BMED360 – In Vivo Imaging and Physiological Modelling, spring 2016
• MAT100 – Grunnleggende matematikk for ingeniører, fall 2015, for students in the electrical engineering programs "Elkraftteknikk" and "Kommunikasjonssystemer"
• MAT106 – Videregående matematikk for elektroingeniører, spring 2015, for students in the electrical engineering programs "Elkraftteknikk" and "Kommunikasjonssystemer"
• MAT100 – Grunnleggende matematikk for ingeniører, spring 2015, for students in the computer science engineering program "Dataingeniør"
• MAT100 – Grunnleggende matematikk for ingeniører, fall 2014, for students in the engineering programs "Produksjonsteknikk" and "Allmenn maskinteknikk"

From 2011 to 2013 I gave the following courses at the Norwegian University of Science and Technology, mainly to students in engineering programs:

• TMA4125 – Matematikk 4, spring 2013
• TMA4100 – Matematikk 1, fall 2012
• MA0002 – Brukerkurs B, spring 2012
• TMA4100 – Matematikk 1, fall 2011

I have been a substitute lecturer in MAT212 – Functions of several variables at the University of Bergen in 2010, and in Les algèbres de Hopf combinatoires en théorie quantique des champs perturbative, Université de Strasbourg, 2009