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The Data Privacy Landscape is Changing | Stats + Stories Episode 183

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Manage episode 290049906 series 1228032
Content provided by Stats + Stories and The Stats + Stories Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stats + Stories and The Stats + Stories Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Privacy is becoming an ever more potent concern as we grapple with the reality that our phones, computers, and our browser histories are filled with data that could reveal a lot about who we are sometimes things we’d rather keep private. The issue of the privacy of data is not a new concern for researchers in fact, whenever someone wants to work with people, oversight boards ask them about how they’ll keep data about participants private. But the data landscape for researchers and statisticians is changing and that’s the focus of this episode of Stats and Stories with guests Claire McKay Bowen and Joshua Snoke. Claire McKay Bowen is the Lead Data Scientist of Privacy and Data Security at the Urban Institute. Her research focuses on comparing and evaluating the quality of differentially private data synthesis methods and science communication. After completing her Ph.D. in Statistics from the University of Notre Dame, she worked at Los Alamos National Laboratory, where she investigated cosmic ray effects on supercomputers. She is also the recipient of the NSF Graduate Research Fellowship, Microsoft Graduate Women’s Fellowship, and Gertrude M. Cox Scholarship. Joshua Snoke is an Associate Statistician at the RAND Corporation in Pittsburgh. His research focuses on applied statistical data privacy methods for increasing researchers’ access to data restricted due to privacy concerns. He has published on various statistical data privacy topics, such as differential privacy, synthetic data, and privacy preserving distributed estimation. He serves on the Privacy and Confidentiality Committee for the American Statistical Association and the RAND Human Subjects and Protections Committee. He received his Ph.D. in Statistics from the Pennsylvania State University.
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432 episodes

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Manage episode 290049906 series 1228032
Content provided by Stats + Stories and The Stats + Stories Team. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Stats + Stories and The Stats + Stories Team or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Privacy is becoming an ever more potent concern as we grapple with the reality that our phones, computers, and our browser histories are filled with data that could reveal a lot about who we are sometimes things we’d rather keep private. The issue of the privacy of data is not a new concern for researchers in fact, whenever someone wants to work with people, oversight boards ask them about how they’ll keep data about participants private. But the data landscape for researchers and statisticians is changing and that’s the focus of this episode of Stats and Stories with guests Claire McKay Bowen and Joshua Snoke. Claire McKay Bowen is the Lead Data Scientist of Privacy and Data Security at the Urban Institute. Her research focuses on comparing and evaluating the quality of differentially private data synthesis methods and science communication. After completing her Ph.D. in Statistics from the University of Notre Dame, she worked at Los Alamos National Laboratory, where she investigated cosmic ray effects on supercomputers. She is also the recipient of the NSF Graduate Research Fellowship, Microsoft Graduate Women’s Fellowship, and Gertrude M. Cox Scholarship. Joshua Snoke is an Associate Statistician at the RAND Corporation in Pittsburgh. His research focuses on applied statistical data privacy methods for increasing researchers’ access to data restricted due to privacy concerns. He has published on various statistical data privacy topics, such as differential privacy, synthetic data, and privacy preserving distributed estimation. He serves on the Privacy and Confidentiality Committee for the American Statistical Association and the RAND Human Subjects and Protections Committee. He received his Ph.D. in Statistics from the Pennsylvania State University.
  continue reading

432 episodes

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