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Deep data from wearable sensors for healthcare

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Topic: Deep data needs and challenges in precision medicine

Speakers: Amir Bahmani, Ph.D., Lecturer and Director of Deep Data Research Center, Genetics, Stanford University

Abstract: We are currently at the beginning stages of a generation-defining revolution in biology. For the past two decades, breakthroughs in our understanding of genetics and genomics, coupled with those in AI and machine learning, have presented us with opportunities to radically improve healthcare around the world. Data is now a digital specimen, but as more and more data is collected, often in different formats and on disparate platforms, new solutions are needed to successfully integrate, store, compute, and secure data. This talk provides a short set of examples for how to handle large-scale medical studies in a secure and scalable fashion. It assesses contemporary realities, identifies potentially promising research directions, and investigates potential impact on the field of bioinformatics from a Computer Science perspective.


“Empathokinaesthetic Sensing”  

Speakers: Bjoern Eskofier, Ph.D., Professor and Head of the Machine Learning and Data Analytics Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg


The talk will give an overview of the collaborative research center “empatho-kinaesthetic sensory science” (, which is newly funded by the German Research Foundation (DFG; 12M€). In EmpkinS, we combine research in traditional wearable sensing with novel (radar-based) sensing concept. I will highlight the interdisciplinary research of engineering, ethics, medical, and psychological experts within in EmpkinS.

The systems that are currently being investigated in EmpkinS in laboratory environments will have everyday applicability in the future. This will open up new possibilities in healthcare, which will hopefully contribute to delivering more objective, precise, and personalized medical diagnosis and care decisions in a future AI-supported healthcare system.

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