Privacy issues are ubiquitous. Though the environment may change, the issues of anonymity, confidentiality, and disclosure control persist. As a discipline, data privacy is related to, but is not encompassed by, data security. One of the core distinctions is that data privacy is strongly entwined with data semantics. The manner by which we learn from data is dependent on what the data reveals about an individual. The development of practical solutions for privacy in the real world requires the engineering of new technology and, in the process of doing so, the development and refinement of computational principles in fields ranging from bioinformatics to complex systems design and analysis. As a consequence, my research has lead to the generalization of privacy models initially designed for DNA databases to other types of biomedical data, as well as the construction of technologies for other data-centric environments, such as biometrics. My investigations bridge the boundaries of engineering, computer science, healthcare, molecular biology, and public policy.

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