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08.05.2019 To 08.05.2019

BEMC Talk, 08.05.2019: Machine learning for population-based health studies

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Event for expert public only

Lecturer: Dr. Christoph Lippert


Berlin is home to many epidemiologists, but there aren’t many local platforms for us to connect, learn new methods, and discuss current issues in the field. The Berlin Epidemiological Methods Colloquium (BEMC) seeks to fill this gap via interactive monthly BEMC Talks and BEMC JClub.

Health data scientist Christoph Lippert works at the Faculty of Digital Engineering, a faculty jointly founded by the University of Potsdam (UP) and the Hasso Plattner Institute (HPI).

As an expert for digital health with an emphasis on machine learning, Lippert’s work will explore the theory of machine learning and artificial intelligence, as well as novel applications in medicine. The focus is on advancing the capabilities to predict personal health risks and supporting the personalized prevention of health issues and diseases.

"In my talk, I’ll introduce our research at the interface of machine learning and statistics towards new methods for large-scale epidemiologic studies. We are working on models and algorithms that allow us to analyze high-dimensional genotypes and phenotypes from imaging and sequencing at scale. I’ll be talking about our work on mixed models for confounder correction, quantitative phenotyping using deep learning, as well as our works on novel statistical tests on deep learning embeddings of images."

Organizational and administrative matters


Dr. Christoph Lippert, Universität Potsdam/Hasso-Plattner-Institut

Event organizer

Berlin Epidemiologic Methods Colloquium




Seminar room of the Neurology Clinic; Bonhoefferweg 3 entrance, 3rd floor, Charité – Campus Mitte


Please register: BEMC Website


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