Dr Axel Oehmichen

Speaker Biography

Dr Axel Oehmichen is a co-founder at start-up called Secretarium (https://secretarium.com/) and assumes the role of Chief Data Science Officer. He is applying his knowledge in distributed computing and privacy to build a confidential computing platform to simplify the setup and integration of privacy-respecting applications in finance and life science. 


Talk Abstract

The emergence of confidential computing (i.e. trusted execution environments and blockchain technologies) and new privacy techniques enable researchers to unlock computing scenarios that have previously not been possible.

Today, most applications encrypt data at-rest and in-transit, but the data must be decrypted for processing. By guaranteeing the data’s security, integrity, and confidentiality (even during processing), it allows the use by other parties of fine-grain data to unlock new insights with consent and without disclosing the data.

The application of artificial intelligence within healthcare and the life sciences represents one of the most exciting and valuable areas of scientific research. With ever-increasing amounts of data available to train new models, and the promise of new medicines and therapeutic interventions, the use of AI within healthcare is expected to provide substantial benefits to patients. Confidential computing allows the federation of data to train those models, thus creating better models. In turn, those models can be rented out to other parties securely and generate new revenue streams for companies which invested in developing those models.

In addition to traditional life science data, new data types such as human mobility data are emerging as new sources for public health research. Human mobility is indisputably one of the main spreading mechanisms of infectious diseases. Therefore, understanding human mobility is essential for forecasting, characterizing and controlling the temporal and spatial spread of infectious diseases during epidemic outbreaks. Access to regulated or commercially sensitive data, such as mobile phone call data records, can unlock new public health research insights and guide policies while protecting companies’ and users’ privacy.


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