7C – Survey Design and Machine Learning

Survey Design and Machine Learning
Presentation & Discussion
7C - Tech


Time/Date
10:45am-12:00pm on Tuesday, 4/21/2026

Facilitator
Deveny Flanagan, University of Minnesota - Office of Measurement Services

This session highlights best practices in scientific research, explores effective survey methodologies, and introduces open-source tools alongside machine learning models.

    Presentations
  • Digital Support for Study Preparation and the Implementation of Good Scientific Practice
    • Roman Auriga, Leibniz Institute for Educational Trajectories (presenter)
    • Nils Lerch, Leibniz Institute for Educational Trajectories
    • Lea Rauh, Leibniz Institute for Educational Trajectories
  • Open-Source Technologies in the U.S. Census Bureau Geographic Partnership Programs Web Applications
    • Emily Vratarich, U.S. Census Bureau (presenter)
  • Combining National-Level Parcel Datasets with Cutting-Edge Machine Learning Models
    • Gustavo Maldonado, U.S. Census Bureau (presenter)
  • Optimizing Enumerator Recruitment for the 2026 Census Test: A Flexible Wage-Setting Approach
    • Ariel Binder, U.S. Census Bureau (presenter)
    • Mark Klee, U.S. Census Bureau
    • Michaela Dillon, U.S. Census Bureau
    • Marisa Hotchkiss, U.S. Census Bureau
    • Gregory Kinney, U.S. Census Bureau