Genomics and digital phenotyping (electronic medical records, imaging, self-reported surveys, etc) have the potential to transform our understanding, diagnosis and treatment of human diseases. Realizing the potential of these rich data requires aggregating and sharing data across individual centers where the data is currently siloed. However, sharing data raises concerns about individual privacy. This workshop will explore the foundational algorithmic challenges of protecting individual privacy in this bio-medical context.
This workshop has a number of aims:
To explore both the theoretical and implementation challenges of emerging techniques for protecting the privacy of genomic and phenotyping data. This will include frameworks such as differential privacy, homomorphic encryption, and multiparty computation, as well as key tasks such as computing summary statistics and associations.
To bring together theorists and practitioners from industry, biobanks and hospitals in order to understand what are the real, actionable challenges in privacy and sharing of bio-medical data.
To formulate key foundational questions about privacy raised through new and emerging technologies such as genome editing or DNA storage.
To develop connections between privacy questions in -omics and notions of overfitting and fairness