CS&E Colloquium: Private Data Exploring, Sampling, and Profiling

The computer science colloquium takes place on Mondays and Fridays from 11:15 a.m. - 12:15 p.m.

This week's speaker, Chang Ge (University of Waterloo, Canada), will be giving a talk titled "Private Data Exploring, Sampling, and Profiling".

Abstract

Data analytics is being widely used in businesses. In many cases, conducting enterprise data analytics faces two practical challenges: 1) the datasets usually contain sensitive and private information and do not allow unfettered access; and 2) these data are often owned by multiple parties and stored in silos with different access control. Therefore, it's often required to do analytics on private siloed data.

In this talk, I discuss the challenges and introduce three systems that enable private data exploring, sampling, and profiling. On private data exploration, I describe our work in APEx for accuracy-aware differentially private data exploration; on private data sampling, I talk about the Kamino system for constraint-aware differentially private data synthesis; and on private data profiling, I introduce our work in SMFD for secure multi-party functional dependency discovery. 

Biography

Chang Ge is a PhD candidate in the Data Systems Group at the University of Waterloo advised by Ihab Ilyas. He is broadly interested in data management, with a recent focus on new algorithms and systems for data analytics in the presence of private and dirty data. He also has been solving data management problems at companies including Apple, Microsoft, IBM, and SAP. He was awarded the Queen Elizabeth II Graduate Scholarship in Science & Technology, and the Cybersecurity and Privacy Excellence Graduate Scholarship from the University of Waterloo.

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Start date
Monday, Feb. 21, 2022, 11:15 a.m.
End date
Monday, Feb. 21, 2022, 12:15 p.m.
Location

Mechanical Engineering 108 or online via Zoom