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Differential Privacy in Practice: Unlocking Insights from Data while Protecting Individual Privacy | Privacy Engineering & Technology Education Discussion (PETed)

July 25 @ 12:00 pm - 1:00 pm UTC-4

Join our IOPD Privacy Engineering & Technology Education Discussion (PETed) Series! The format of the webinar will be a recorded 10-minute introduction followed by a 40-minute informal discussion and interaction with members of the IOPD. The goal will be a discussion on how to solve a specific privacy problem or privacy related resource topic and the latest implementation techniques for some of the biggest challenges like synthetic data, zero-knowledge proofs, homomorphic encryption, and translucent databases.

The participants will be asked to bring questions related to the topic. Come back the fourth Thursday of every month for a new discussion, new speaker, and new insights on the most cutting-edge privacy challenges!


Date & Time:

July 25, 2024 @ 12:00 PM EDT / 6:00 PM CEST



How to deploy differential privacy in practice to unlock insights from sensitive, regulated, or proprietary data. 



In this talk Gerome will explain how we have successfully used differential privacy to unlock insights from highly sensitive data. This will include examples of practical deployments of the technology at major enterprises: the challenges, solutions, and lessons learned. Gerome will describe the benefits differential privacy can offer to a data custodian who is responsible for the management of sensitive data, including clarity about the privacy risk involved in a data release and the ability to share higher-quality data.


Problem Statement:

Differential privacy allows sensitive data to be shared in a manner that preserves insights in the data while offering a rigorous guarantee of protection for contributing individuals.


Pre-Discussion Resources:



Gerome Miklau

Gerome Miklau is co-founder and CEO of Tumult Labs, a start-up focused on commercializing privacy technology. He is on leave from his position as a Professor of Computer Science at the University of Massachusetts, Amherst. Prior to founding Tumult Labs, he consulted for the U.S. Census Bureau on disclosure avoidance algorithms used for the 2020 Decennial Census.

His academic research focuses on private, secure, and equitable data management. He designs algorithms to accurately learn from data without disclosing sensitive facts about individuals, primarily in the model of differential privacy. He studies fair and responsible data management. He has also designed novel techniques for controlling access to data, limiting retention of data, and resisting forensic analysis.

He received his Ph.D. in Computer Science from the University of Washington in 2005. He earned Bachelor’s degrees in Mathematics and in Rhetoric from the University of California, Berkeley, in 1995.



Mary Yip

Mary is a privacy officer who is passionate about privacy and data protection. She is responsible for the oversight of privacy compliance and privacy risks management for several entities within her organization. Mary’s diverse experience in privacy, risk management, auditing, business analysis, and project management contributes to her effectiveness in leading and supporting privacy programs across entities.


The IOPD Privacy Engineering & Technology Education Discussion (PETed) Series is a members-only event. Join as an Ambassador before the 1st of each month to get invited to this month’s event! Please reach out to a current member to be invited as a guest. If you are already a member, subscribe to our PETed Mailing List for announcements and monthly invitations!


July 25
12:00 pm - 1:00 pm UTC-4
Event Category:



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