The University of Texas at Austin McCombs School of Business
The University of Texas at Austin McCombs School of Business

High-performance organizations depend upon actionable insights from data to drive business forward. As the collection and use of “big data” becomes more prevalent, data privacy becomes a central concern to a variety of internal and external stakeholders.

Responsible firms put an emphasis on the conscientious use of data. Methods of differential privacy enable firms to learn from the data while protecting personal and private information. 

This conference will provide a primer on differential privacy, exploring its methods, best practices, and current research.

Don Brown
RESERVE YOUR SEAT
Don Brown

Field CTO,
Synthesized

Nov. 17–18, 2022
Online Event | Confirmation Sent Upon Registration

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Research Meets Practice 
Industry practitioners, academic researchers, and students of all ages, backgrounds, and disciplines are invited to attend this online conference. Registration is complimentary.

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© 2022 McCombs School of Business, The University of Texas at Austin

Agenda   Speakers  |  Register

Agenda

1pm:

Read Bio
Sree Nagarajan

Founder and CEO,
Affinity Answers

Sree Nagarajan
Read Bio
David Hendrawirawan

Director, Data Integrity First, Lecturer, McCombs School of Business

David Hendrawirawan
Read Bio
Michael Shepherd

Distinguished Engineer,
Dell Technologies

Michael Shepherd
Read Bio
Venkat Achanta
Venkat Achanta

Executive Vice President and Chief Data and Analytics Officer,
TransUnion

Read BioRead Bio
Eric Seufert

Analyst and Strategy Consultant,
Heracles Media

Eric Seufert
David Wu
David Wu

Assistant Professor of Computer Science,
University of Texas at Austin

Read BioRead Bio
Adam Smith

Professor of Computer Science and Engineering,
Boston University

Adam Smith
Daniel Mitchell

Associate Director, Center for Analytics and Transformative Technologies, McCombs School of Business
University of Texas at Austin

Program Committee

Speakers/Panelists

Sponsors

Read Bio
Wanrong Zhang

Computing Innovation Fellow,
John A. Paulson School of Engineering and Applied Sciences,
Harvard University

Wanrong Zhang

CATT 2022 GLOBAL ANALYTICS CONFERENCE

DIFFERENTIAL PRIVACY

How do you generate and share insights from data while protecting individual privacy?

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Nov. 17–18, 2022 | Online

Michael Sury

Director, Center for Analytics and Transformative Technologies, McCombs School of Business
University of Texas at Austin

Lillian Mills

Dean, McCombs School of Business,
University of Texas at Austin

Lillian Mills Headshot
Read Bio
Susan Broniarczyk 

Associate Dean for Research, McCombs School of Business,
University of Texas at Austin 

Kumar Muthuraman  

Faculty Director, Center for Analytics and Transformative Technologies, McCombs School of Business
University of Texas at Austin

Thursday, Nov. 17

Friday, Nov. 18

Panel, Differential Privacy: Business Case and Best Practices

Moderator,

Sree Nagarajan, Affinity Answers, Journey Towards Ethical Privacy: The Story of a Reformed Data Provider

8:30 am:

Michael Shepherd, Dell, WEB3: A Foundation Built on Data Ownership and Privacy

Cynthia Dwork, Harvard

2pm:

3pm:

4pm:

Opening Remarks from Dean Mills and Conference Chair Dan Mitchell

12:30 pm:

12:45 pm:

Cynthia Dwork
Cynthia Dwork

Gordon McKay Professor of Computer Science,
Harvard Law School

Read BioRead Bio
Bill King

Managing Partner,
MoviPartners

Bill King
Robert Stratton
Robert Stratton

SVP, Data Science,
Neustar, Inc., a TransUnion company

Read Bio

Venkat Achanta, Transunion, Applying Privacy Preserving Technologies at Scale

Wanrong Zhang, Harvard, Composition Theorems for Interactive Differentially Private Mechanisms

David Hendrawirawan, UT McCombs and Data Integrity First, Introduction to Differential Privacy

Room Opens

Don Brown, Synthesized

Panelists,

Robert Stratton, Transunion

Bill King, Movi Partners

Eric Seufert, Heracles Media

9:30 am:

David Wu, UT Computer Science, Computing on Private Data: Genome Privacy Using Cryptography

10:30 am:

Adam Smith, Boston University, When is Memorization Necessary for Machine Learning?

11:30 am:

KEYNOTE

KEYNOTE