On Wednesday, February 19, at 17:30 GMT+2 we will hear two talks on #Federated Learning:

Talk 1

Dr. Anne Hartebrodt, "Federated Learning for Data Privacy in Biomedicine", Friedrich-Alexander Universität Erlangen-Nürnberg, Germany

Keywords: Federated Learning, Data privacy

Abstract: Federated Learning (FL) has been promoted as a privacy-preserving alternative to centralized data analysis. In this talk, the concept of federated learning will be discussed and the potential impact FL may have for understanding medical conditions. Privacy and Security aspects of FL will be discussed.

Talk 2

Dr. Florian R. Hölzlwimmer, "GHGA - The German Human Genome-Phenome Archive", GHGA and Technical University Munich, Germany

Keywords: Genome Archive, FAIR, Data sharing

Abstract: Since the human genome was fully decoded in 2003, next-generation sequencing (NGS) is now used in almost any genetic-based research project. Over the past decades, the sequencing costs of a single base outpaced Moor’s law, leaving the community with a considerable amount of data in the range of petabytes per year to be processed, harmonized, and archived. The German Human Genome-Phenome Archive (GHGA, www.ghga.de) aims to tackle these problems and make this data FAIR (Findable, Accessible, Interoperable, and Reusable) for the research community. Making research data FAIR comes along with the standardization of data processing. Within GHGA, the processing of this data is planned using a federated IT infrastructure across Germany’s research institutes.

Format: Online, free to attend, no registration is required: Zoom

Organization: YMS is organized by RSBI and is linked to RoBioinfo Seminars

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