Projects

All projects Privacy Protection & CryptographyBlockchains & Smart ContractsSoftware VerificationDevice & System SecurityMachine LearningFinanceHealthGovernment & HumanitarianCritical InfrastructureDigital Information
Mar 2019 → Mar 2020 Project

MedCo: Collective Protection of Medical Data

Partner: CHUV
Partner contact: Nicolas Rosat, Jean-Louis Raisaro
EPFL laboratory: Laboratory for Data Security (LDS)
EPFL contact: Prof. Jean-Pierre Hubaux

MedCo, developed in the LDS lab of professor Jean-Pierre Hubaux in collaboration with professor Bryan Ford’s DEDIS lab and the Lausanne University Hospital (CHUV), is the first operational system that makes sensitive medical-data available for research in a simple, privacy-conscious and secure way. It enables hundreds of clinical sites to collectively protect their data and to securely share them with investigators, without single points of failure. MedCo applies advanced privacy-enhancing techniques, such as: Multi-party homomorphic encryption, Secure distributed protocols and Differential privacy.

TopicsPrivacy Protection & CryptographyHealth

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Jan 2019 → Dec 2021 Project

Monitoring, Modelling, and Modifying Dietary Habits and Nutrition Based on Large-Scale Digital Traces

Partner: Microsoft
Partner contact: Ryen W. White
EPFL laboratory: Data Science Lab
EPFL contact: Prof. Robert West, Kristina Gligoric

The overall goal of this project is to develop methods for monitoring, modeling, and modifying dietary habits and nutrition based on large-scale digital traces. We will leverage data from both EPFL and Microsoft, to shed light on dietary habits from different angles and at different scales. Our agenda broadly decomposes into three sets of research questions: (1) Monitoring and modeling, (2) Quantifying and correcting biases and (3) Modifying dietary habits. Applications of our work will include new methods for conducting population nutrition monitoring, recommending better-personalized eating practices, optimizing food offerings, and minimizing food waste.

TopicsMachine LearningHealth

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Apr 2018 → Dec 2021 Project

Data Protection in Personalized Health

Partner: CHUV, ETH
Partner contact: Prof. Jacques Fellay (EPFL/CHUV), Prof. Effy Vayena (ETH)
EPFL laboratory: Laboratory for Data Security (LDS)
EPFL contact: Prof. Jean-Pierre Hubaux

P4 (Predictive, Preventive, Personalized and Participatory) medicine is called to revolutionize healthcare by providing better diagnoses and targeted preventive and therapeutic measures. In order to enable effective P4 medicine, DPPH defines an optimal balance between usability, scalability and data protection, and develops required computing tools. The target result of the project will be a platform composed of software packages that seamlessly enable clinical and genomic data sharing and exploitation across a federation of medical institutions across Switzerland. The platform is scalable, secure, responsible and privacy-conscious. It can seamlessly integrate widespread cohort exploration tools (e.g., i2b2 and TranSMART).

TopicsPrivacy Protection & CryptographyMachine LearningHealth

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