I am passionate about the human genome and its regulation, as well as drug discovery. My research lies at the interface of biology, artificial intelligence (machine learning), and statistics. During my PhD I integrated biological data sets (e.g. gene expression) and chemical properties of drug candidates in predictive models of compound activity. This approach permits to uncover new therapeutical targets and drugs, as well as to improve the current state of the art of virtual screening approaches. I am currently working on the analysis of next generation sequencing data (WES and WGS) from cancer patients and neurological diseases generated by The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), Pan-Cancer Analysis of Whole Genomes (PCAWG), and Brain Somatic Mosaicism (BSM) Network.