I’m an Industrial PhD Student at Novo Nordisk R&ED and DTU. During my studies and participation in multiple research projects, I have gathered experience with several bioinformatics & AI methodologies applied to life science data.
The research projects cover multiple fields within bioinformatics, including:
- Childhood cancer genomics
- Structure-based B-cell epitope prediction
- Bayesian genotype-phenotype correlation
- Machine-learning (ML)-based polygenic risk scores for obesity, and
- Explainable disease progression prediction from electronic health record data
I am deeply passionate about leveraging AI methodologies to extract comprehensive insights from big data in life science, for the purpose of enhancing target discovery, deepening disease understanding, and ultimately improving patient outcomes.