July 18, 2016, Darmstadtium, Darmstadt, Germany
Medical progress increasingly depends on analyzing large data sets. This is often prevented by data silos and stringent privacy requirements. New technologies are emerging that allow privacy-preserving collaborative analytics of medical data, even if the amounts of data are large, the security and privacy requirements remain stringent, and the data origins from multiple silos. In particular fields with highly sensitive data such as genomics or other health domains, the wide range of privacy-preserving analytics technologies promise to enable new and exciting applications and scientific breakthroughs.
- Jim Davies (Genomics England Limited and Oxford University):
“Security and Privacy in the UK: The 100,000 Genomes Project”
- Roland Eils (German Center for Cancer Research (DKFZ) and University of Heidelberg): “Curse or Cure: Big Data in Health”
- Paul Francis (MPI-SWS and Aircloak): “A Breakthrough in Anonymity X Utility for Anonymized Analytics”
- Kate Black (23andMe): Title tba
- To bring stakeholders from Medicine, Law, and Technology together to get a better understanding of the full range of requirements, capabilities, and constraints.
- To compare and contrast recent advances from a user perspective and to identify promising directions for further research and real-world validation.
- Discuss the current state of technology and to identify remaining technical and non-technical hurdles for public adaption.
Poster Submission, Logistics and Registration:
- Date and Venue: July 18, 2016 at the Darmstadtium, Darmstadt, Germany
- Logistics and Registration: spw2016.de (Register for SPMED; regular 90EUR, Student 60EUR).
- Call for Posters that discuss related research. Please submit A0 posters by email before June 20 (notification June 30). The workshop will not publish proceedings: The goal is to openly share and summarize progress and insights.
Organizers: Ahmad-Reza Sadeghi, TU Darmstadt and Center for Advance Security Research Darmstadt (CASED), Emiliano De Cristofaro (University College London), Jason Flannick (Eli and Edythe L. Broad Institute of Harvard and MIT), Michael Steiner and Matthias Schunter (Intel Labs). For inquiries or any other questions, please contact [email protected]