My background is in bioinformatics and computational biology with a strong interest in quantative modeling and the analysis of large scale molecular data.

Research

I am interested in building new models for data integration and in the data analysis of molecular data of cancer patients. As the computational biology subteam lead of the Tumor Profiler consortium I am actively working and coordinating the development of scalable approaches to integrate single cell measurements and train predictive models that enable the in-depth analysis of patient data in order to derive clinically relevant insights. I am especially excited about development of new approaches for the analysis of mutational signatures and have joined the ICGC-ARGO mutational signature working group.

Scientific Background

I attained my undergraduate degree in bioinformatics from the Friedrich-Schiller-University in Jena, Germany. During this time, I attended a summer research program program at Forschungszentrum Juelich working on scalable parameter estimation methods. I received my PhD in Computational Biology from the University of Southern California, developing a variant interpretation approach for non-coding variants as well as working on linear mixed models to analyze transcriptome data. In 2013, I joined the Rätsch group at Memorial Sloan Kettering Cancer Center in New York contributing towards large-scale cancer genomics efforts such as TCGA PanCanAtlas and ICGC Pan-Cancer Analysis of Whole Genomes Working Group.