Projects
Ongoing projects
Data-Driven Games. Game development is a particularly interesting design challenge because it requires the design team to have expertise in many different areas: art, music, engineering and so on. Historically, game developers have solved this problem by separating game content from game code; games designed this way are called data-driven . In this project we are working to further the development of data-driven games by adapting techniques from the data management community and applying them to game development. Databases have revolutionized the design of data-driven business applications because they separate the processing of data from its specification. SImilarly, our goal is develop a general framework that allows game designers to specify game behavior without having to worry about how to implement it efficiently.
Data Privacy. The digitization of our daily lives has led to an explosion in the collection of personal data by governments, corporations, and individuals. Such information is stored in large databases. This has led to easy access to sensitive personal information, resulting in a dramatic increase in the disclosure of sensitive information. Hence it is crucial to design database systems which can limit the disclosure of private information. At the Database Privacy Group @ Cornell, we research various aspects of the privacy problem including formal definitions of privacy, efficient algorithms for checking various definitions of privacy, the trade-off between privacy and utility, and apply this to different settings like privacy preserving data mining and data publishing.
Youtopia: Causal Databases. Database users increasingly expect to work with, create, and query not just data, but rich and expressive metadata as well. One particular flavor of metadata that is increasingly important in real-world applications is causal metadata. This describes the causal structure, provenance and other causal constraints associated with the data. In the Youtopia project, we are laying the foundations for a new breed of databases -- causal databases. Causal databases can model causal information explicitly, and allow for queries regarding causality and explanations, as well as supporting emerging applications that make use of causality information in novel ways.