Projects

VerdictDB: Universal Approximate Query Processing

Despite 25 years of research in academia, approximate query processing (AQP) has had little industrial adoption, mostly due to the reluctance of traditional vendors to make radical changes and also due to the tight integration with specific platforms. Our proposal, called VerdictDB, uses a middleware architecture that requires no changes to the backend database, and …

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Self-learning Data Systems

Database systems are becoming increasingly complex. Manually configuring a system for each different system environment is too time-consuming and, more than often, not even optimal. To build self-optimizing systems, I am investigating machine learning-based techniques that can continuously optimize the internals of data systems.

Visualization-Aware Sampling

You have billions of data points, but are you frustrated simply because they are just too big to visualize? This is a common problem we encounter when we work with large databases: my dataset is simply too big to interactively explore and gain useful insights from them. Our proposed approach, Visualization-Aware Sampling (VAS), makes the interactive visualization of big data possible …

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hello projects

This is the first post in the project category. Apparently, we don’t have anything to tell you yet!