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I am a postdoctoral researcher in cancer proteomics, with background in medicine and epidemiology. I defended my PhD thesis at the Karolinska Institute in 2023, on . I am skilled in proteomics, proteogenomics, research design, ̽����ѡ statistics, machine learning, and bioinformatics.

My research has two aims:

1) Discovering protein biomarkers for predicting clinical outcomes, such as treatment response, progression, or survival. Our aim is to connect proteomic data to other data modalities for the aim of stratifying cancer patients, to improve clinical decision-making in patient management, primarily in treatment management. I am focused on three highly malignant cancers - glioblastoma, lung cancer, and melanoma and work mainly on plasma proteomics, i.e. analysing hundreds or thousands of proteins that are freely circulating in the liquid component of the blood called plasma.

2) Translating discovery proteomic findings to the clinic. Our aim is to build a clinical proteomics infrastructure for testing and validating new protein biomarkers, for the final goal of integrating research findings in clinical routine.

• Director and examiner for the KI PhD course K7F3120 in Omics Data Analysis: From Quantitative Data to Biological Information.
• Teaching experimental design and data analysis, KI PhD course K7F255 in Proteomics by Mass Spectrometry: When and How.