Steinar Laenen

Steinar Laenen

PhD Candidate Theoretical Computer Science

University of Edinburgh


I am a first year PhD student at the Laboratory for Foundations in Computer Science, in the School of Informatics at the University of Edinburgh. I am supervised by Dr. He Sun.

Before that I was a research intern at Five, in their Oxford research group, where I worked on few-shot learning together with Dr. Luca Bertinetto

I received my MSc in Artificial Intelligence graduate (with distinction) from the University of Edinburgh. For my thesis I received the Joint AI MSc Dissertation Prize, awarded to 2 out of 200+ students. I did my bachelors (summa cum laude) in mathematics and computer science at Amsterdam University College.

My current research focuses on developing (fast) clustering algorithms for graphs, using techniques from spectral graph theory.

  • PhD in Theoretical Computer Science, 2021 - present

    University of Edinburgh

  • MSc in Artificial Intelligence, 2018 - 2019

    University of Edinburgh

  • BSc in Liberal Arts and Science, Maths and Computer Science, 2015 - 2018

    Amsterdam University College


Research Intern
Dec 2019 – Dec 2020 Oxford, UK
Researched few-shot learning for image classification at FiveAI`s Oxford research group, which has close ties to the Torr Vision Group at Oxford University. The work I did together with Luca Bertinetto resulted in a contributed talk at the NeurIPS 2020 Meta Learning workshop, and a NeurIPS 2021 paper.
Warm Arctic
Summer Intern
Jul 2018 – Aug 2018 Reykjavik, Iceland
I worked on a project where we used drones equipped with RGB and infrared cameras to create orthomosaic maps of areas that contain geothermal lineaments. I developed an anomaly detection tool to automatically detect areas of geothermal importance using deep autoencoders and a one-class SVM. This work got published at the Stanford workshop on Geothermal Reservoir Engineering.
University of Reykjavik
Software Engineering Intern
Jul 2017 – Aug 2017 Reykjavik, Iceland
Worked on a project which aimed to research the importance of bodily cues in social interaction. The work consisted of designing and programming automated intelligent social behaviour for virtual agents in Unity3D and C#. Constructed complex social behaviours for virtual agents such as glancing, conversing, and gesticulating. This work got published at a virtual agents conference.