Daniel Bakkelund – PhD Candidate

Data Science


Project: “Increasing the power of statistical algorithms in machine learning through augmentation with ontology theory“.

Scientific interests: Mathematical modelling, statistical modelling and probability, order theory, discrete mathematics, graph- and network theory, especially ordered structures, graph- and network comparison, clustering theory and applying axiomatic-deductive methods for solving real-world problems through proven theories and algorithms.

What triggers me scientifically: Problems that lie in the crossing between applications and theoretical mathematical research, where the existing theoretical machinery for solving the applied problem doesn’t exist, and has to be developed.