Affiliated Faculty
Stefan Konigorski
Senior Researcher
Bio
Stefan Konigorski, PhD, is a Senior Researcher in the Digital Health & Machine Learning group at the Hasso Plattner Institute, and Adjunct Assistant Professor in the Genetics and Genomic Sciences Department at the Icahn School of Medicine at Mount Sinai. He develops statistical and machine learning methods to derive causal effects from complex observational and experimental studies, with a specific research focus on investigating personalized health trajectories and digital health interventions by using N-of-1 trials. Dr. Konigorski received a Diplom in Mathematics from the University of Heidelberg and M.Sc. in Biostatistics from the University of Toronto, while working in Toronto at the Mount Sinai Hospital and Dalla Lana School of Public Health. Before joining the HPI in 2019, he obtained his PhD from the Humboldt University of Berlin in Computer Science, in which he developed and applied novel statistical methods based on copula functions and estimating equations that improved the power of state-of-the-art association tests of molecular omics data at the Max Delbrück Center for Molecular Medicine.
Bio
Stefan Konigorski, PhD, is a Senior Researcher in the Digital Health & Machine Learning group at the Hasso Plattner Institute, and Adjunct Assistant Professor in the Genetics and Genomic Sciences Department at the Icahn School of Medicine at Mount Sinai. He develops statistical and machine learning methods to derive causal effects from complex observational and experimental studies, with a specific research focus on investigating personalized health trajectories and digital health interventions by using N-of-1 trials. Dr. Konigorski received a Diplom in Mathematics from the University of Heidelberg and M.Sc. in Biostatistics from the University of Toronto, while working in Toronto at the Mount Sinai Hospital and Dalla Lana School of Public Health. Before joining the HPI in 2019, he obtained his PhD from the Humboldt University of Berlin in Computer Science, in which he developed and applied novel statistical methods based on copula functions and estimating equations that improved the power of state-of-the-art association tests of molecular omics data at the Max Delbrück Center for Molecular Medicine.