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EVENT DETAILS |
Do intervention programs really make a difference? Evaluating the effect of an intervention on a system, such as changing recruitment practices at a company, modifying a production process, or introducing masks in response to Covid-19, is pervasive across all data-driven disciplines. In his presentation, Dr. Stefan Konigorski will focus on interventions in the biomedical arena, where medical treatments & behavioral changes are the primary focus.
Specifically, Dr. Konigorski will discuss data-driven evidence that an intervention works for a specific individual, & which intervention works best. He will speak about N-of-1 trials, which are formally multi-crossover trials within individuals. Digital N-of-1 trials are at the intersection of personalized clinical care & research & can transform medical practice. He will also present the StudyU platform, which Dr. Konigorski & his colleagues developed at HPI. StudyU allows medical researchers to easily design & run personalized trials.
Biography
Stefan Konigorski, PhD, is a Senior Researcher in the Digital Health & Machine Learning group & Head of the Health Intervention Analytics lab (https://hpi.de/lippert/health-intervention-analytics-lab.html) at the Hasso Plattner Institute in Potsdam, Germany. He is also an Adjunct Assistant Professor in the Genetics & Genomic Sciences Department at the Icahn School of Medicine at Mount Sinai in New York. Dr. Konigorski is currently a visiting faculty member in the Department of Statistics at Harvard University. In his current research, he is developing computational tools & statistical methods for designing modern trials & estimating causal effects from them, with a specific focus on investigating personalized digital health interventions by using N-of-1 trials & micro-randomized trials.
Dr. Konigorski received his Diplom in Mathematics from the University of Heidelberg & an M.Sc. in Biostatistics from the University of Toronto. He obtained his PhD from the Humboldt University of Berlin in Computer Science, in which he developed & applied novel statistical methods based on copula functions & estimating equations for genetic & molecular association tests.
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