Niklas Wahlström is an Assistant professor at the Division of Systems and Control, Department of Information Technology at Uppsala University. Dr Wahlström joined WASP in 2019.
Main supervisor for one industrial PhD student and co-supervisor for one academic PhD student, both within WASP Graduate School.
To get access to an excellent network of researchers and for the great funding possibilities.
WASP brings together researchers and collaborators from both academia and industry in a unique network. It provides great initiatives, such as the graduate school.
Physics-informed machine learning, i.e., how to leverage data-driven machine learning models using domain knowledge.
Machine learning models are used in many different applications, for example, indoor localization using magnetic fields, target tracking using magnetic sensors, and automatic control based on raw pixel data, to mention a few where I have been involved. By leveraging these models with domain knowledge, even better performance can be achieved in these applications.
By making machine learning models more physics-informed, they will also become more interpretable. This interpretability can transform these machine learning models from being black-box models into full-fledged scientific tools enabling new knowledge discoveries in the scientific domains in which they are employed.