C. Bowen

Most-cited papers

Comparative Study of Differentially Private Data Synthesis Methods
C. Bowen, Fang Liu
2016Statistical Science79 citations Open access
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Comparative Study of Differentially Private Synthetic Data Algorithms from the NIST PSCR Differential Privacy Synthetic Data Challenge
C. Bowen, Joshua Snoke
2019Journal of Privacy and Confidentiality64 citations Open access
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Partitioning a Large Simulation as It Runs
Kary L. Myers, E. Lawrence, M. Fugate, C. Bowen +4 more
2014Technometrics30 citations Open access
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Differentially Private Data Synthesis Methods
C. Bowen, Fang Liu
201617 citations
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Toward a 21st Century National Data Infrastructure
C. Bowen, Robert M. Goerge, Cornell Tech, Mark L. Watson +3 more
202215 citations
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Differentially private data release via statistical election to partition sequentially
C. Bowen, Fang Liu, Bingyue Su
2020Metron13 citations Open access
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A Synthetic Supplemental Public Use File of Low-Income Information Return Data: Methodology, Utility, and Privacy Implications
C. Bowen, V. Bryant, Leonard Burman, S. Khitatrakun +4 more
2020Privacy in Statistical Databases12 citations
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A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses with Evaluations on Administrative and Survey Data
Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke, C. Bowen
2021Journal of the American Statistical Association10 citations Open access
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How Statisticians Should Grapple with Privacy in a Changing Data Landscape
Joshua Snoke, C. Bowen
202010 citations Open access
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A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses for Administrative Tax Data
Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke, C. Bowen
20219 citations
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Differentially Private Generation of Social Networks via Exponential Random Graph Models
Fang Liu, E. Eugenio, I. Jin, C. Bowen
2020Annual International Computer Software and Applications Conference9 citations Open access
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Advancing microdata privacy protection: A review of synthetic data methods
Jingchen Hu, C. Bowen
2023WIREs Computational Statistics8 citations
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Synthetic Individual Income Tax Data: Methodology, Utility, and Privacy Implications
C. Bowen, V. Bryant, Leonard Burman, John Czajka +9 more
2022Privacy in Statistical Databases8 citations
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The promise and limitations of formal privacy
Aaron R. Williams, C. Bowen
2023WIREs Computational Statistics6 citations Open access
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Synthetic Individual Income Tax Data: Promises and Challenges
C. Bowen, V. Bryant, Leonard Burman, S. Khitatrakun +4 more
2022National tax journal6 citations
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The art of data privacy
C. Bowen
2022Significance5 citations
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Protecting Your Privacy in a Data-Driven World
C. Bowen
20214 citations
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STatistical Election to Partition Sequentially (STEPS) and Its Application in Differentially Private Release and Analysis of Youth Voter Registration Data
C. Bowen, Fang Liu
20184 citations
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Incompatibilities Between Current Practices in Statistical Data Analysis and Differential Privacy
Joshua Snoke, C. Bowen, Aaron R. Williams, Andrés F. Barrientos
2023Journal of Privacy and Confidentiality3 citations Open access
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Diﬀerentially Private Methods for Validation Servers
Andrés F. Barrientos, Aaron R. Williams, C. Bowen, J. Abowd +19 more
20213 citations
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The Case for Researching Applied Privacy Enhancing Technologies
C. Bowen, Joshua Snoke, Aaron R. Williams, A. Barrientos
2024Social Science Research Network2 citations Open access
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Differentially Private Synthesis and Sharing of Network Data via Bayesian Exponential Random Graph Models.
E. Eugenio, Fang Liu, Ick Jin, C. Bowen
2021Proposed for presentation at the Joint Mathematical Meetings (In person and Virtual) held January 5-8, 2022 in Seattle, WA.2 citations Open access
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Government Data of the People, by the People, for the People: Navigating Citizen Privacy Concerns
C. Bowen
2024Journal of Economic Perspectives1 citations Open access
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But Can You Use It? Design Recommendations for Differentially Private Interactive Systems
Liudas Panavas, Joshua Snoke, Erika Tyagi, C. Bowen +1 more
2024arXiv.org1 citations
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Editorial: Symposium Data Science and Statistics 2022
C. Bowen, M. Grosskopf
2023Journal of Data Science1 citations Open access
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Why Is Data Privacy Important?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World1 citations
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Differential Privacy: What Is It?
Joshua Snoke, C. Bowen
20191 citations
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Comparative Study of Differentially Private Synthetic Data Algorithms and Evaluation Standards
C. Bowen, Joshua Snoke
2019arXiv.org1 citations
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Differentially Private Release and Analysis of Youth Voter Registration Data via Statistical Election to Partition Sequentially
C. Bowen, Fang Liu
20181 citations
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Building the Census, Block by Block
C. Bowen
2026Issues in science and technology0 citations
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The Future of Public Data Lies in the States, But It’s Complicated
C. Bowen
2026Issues in science and technology0 citations
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Auerbach et al.’s contribution to the Discussion of 'Independent review of the UK Statistics Authority' by Denise Lievesley
Jonathan Auerbach, May H. Aydin, C. Bowen, Constance F. Citro +3 more
2024Journal of the Royal Statistical Society: Series A (Statistics in Society)0 citations
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Editorial: Symposium on Data Science and Statistics 2022
C. Bowen, M. Grosskopf
20230 citations
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The Autonomy Gap: Response to Citro et al. and the statistical community
C. Bowen
2023Statistics and Public Policy0 citations Open access
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Expectations for the 2020 Decennial Census and How They Stood Up to Scrutiny.
Isabel Youngs, Christopher Dick, R. Prevost, C. Bowen
2022International Journal of Population Data Science0 citations Open access
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Using Differential Privacy to Advance Rural Economic Development
C. Bowen, A. Narayanan
20210 citations
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What Is the Future of Data Privacy?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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How Did Data Privacy Change Over Time?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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What Data Privacy Laws Exist?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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What Makes Datasets Difficult for Data Privacy?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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How Do Data Privacy Methods Avoid Invalidating Results?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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How Do Data Privacy Methods Expand Access to Data?
C. Bowen
2021Protecting Your Privacy in a Data-Driven World0 citations
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Data Privacy via Integration of Differential Privacy and Data Synthesis
C. Bowen
20180 citations
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Are more of my patients developing side effects than expected?
C. Bowen, Fang Liu, J. Wheeler
2015Practical Radiation Oncology0 citations
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