Jeremy Seeman

Hello! I am a Data Science Fellow within Michigan Institute for Data Science (MIDAS) at the University of Michigan. I am also affiliated with the Survey Research Center at the Institute for Social Research and the Center for Ethics, Society, and Computing (ESC). 

I work with faculty at ISR and the Dept. of Biostatistics, specifically Yajuan Si, Trivellore Raghunathan (Raghu), and Margaret Levenstein. I recently graduated with my PhD in statistics from Penn State University.  

Recent news: 

• 2024-02:

  • Our paper "Privacy's Odd Couple: Privacy Law and Privacy Engineering on Inference and Information Recovery" (w/ Palak Jain and Daniel Susser) will be presented at Privacy Law Scholar's Conference.

  • Our paper "Differentially Private Population Quantity Estimates via Survey Weight Regularization" (w/ Yajuan Si and Jerome Reiter) will be presented at an upcoming NBER Workshop on Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences.

  • I joined the Program Committee for ACM FAccT.

• 2023-12:

  • Our paper "An Exploratory Meta-Analysis to Identify Outlying Behavior in the NIST Collaborative Research Cycle Archive" with (amazing) undergrad Dhruv Kapur was accepted to the NIST Collaborative Research Cycle Explanatory Workshop on December 18th. 

• 2023-11:

  • I'm honored to receive a Institute for Mathematical Statistics Junior Researcher Travel Award to attend the International Conference in Statistics and Data Science next month in Lisbon, Portugal! I'll be talking about my work on private treatment assignment.

  • I gave a talk at the Michigan Program in Survey and Data Science (MPSDS) and Joint Program in Survey Methodology (JPSM) Seminar Series [slides].

• 2023-10:

  • New preprint: "Privately Answering Queries on Skewed Data via Per Record Differential Privacy" with William Sexton, David Pujol, and Ashwin Machanavajjhala at Tumult Labs. They'll be discussing this work applied to the U.S. Census Bureau's County Business Patterns (CBP) dataset at the 2023 Federal Committee on Statistical Methodology (FCSM) Research and Policy Conference in late October [preprint].

• 2023-09:

  • I gave a keynote talk, "Interfacing Statistics and DP: Method and Mess," and presented two posters at Theory and Practice of Differential Privacy (TPDP) [keynote_slides].

  • I am now an Associate Editor for Statistics and Public Policy.

  • Our work with Daniel Susser, "Between Privacy and Utility: On Differential Privacy in Theory and Practice," was accepted at ACM Journal of Responsible Computing [preprint][DOI]. 

• 2023-08: 

  • I started my new position at UMich!