Academic interests
Symbolic regression, mathematical modeling and large language models (LLMs).
Background
Håkon completed his Master of Science in Applied Physics and Mathematics at the Norwegian University of Science and Technology (NTNU) in 2023 with a main profile in applied physics. For his thesis Håkon parallelized a stochastic, hybrid cellular automaton model of personalized breast cancer therapy that combined discrete and continuous elements. This allowed simulations of a clinically relevant cancer size of a full biopsy, roughly 500 times larger than previously achieved.
PhD project
“Learning differential models (and other logic rules) from data with uncertainty”
Håkon aims to develop new methods within symbolic regression to find mathematical equations on human-understandable form, describing the underlying structure of systems, such as breast cancer.
Supervisors
- Arnoldo Frigessi, University of Oslo, Institute of Basic Medical Sciences
- Alvaro Köhn-Luque, University of Oslo, Institute of Basic Medical Sciences
- Benjamin Ricaud, University of Tromsø, Department of Physics and Technology