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Introducing the CSDE 2024-2025 T32 Fellow Cohort

Posted: 6/26/2024 ()

CSDE is pleased to introduce the 2024-2025 Data Science and Demography Training T32 Fellowship Program Cohort!

 

 

    • Fellow: Courtney Allen
      • Department: Sociology 
      • Adviser: Sara Curran
      • Research: Courtney’s research uses archival data sources, censuses, and vital registration data to study the historic process of hospital desegregation in the U.S. and it’s immediate and long-term impacts on population health.
    •  Fellow: David Coomes
      • Department: Epidemiology
      • Adviser: Stephen Mooney
      • Research: David’s research focuses on rural health disparities, namely, the role of migration in shaping population health and the rural mortality penalty
    • Fellow: Jane Dai
      • Department: Health Systems and Population Health 
      • Adviser: Jesse Jones-Smith
      • Research: Jane will use non-traditional and person-centered data sources to explore how gentrification shapes population health by impacting social environments, built environments, and food systems.
    •  Fellow: Tom Lindman
      • Department: Public Policy & Management
      • Adviser: Heather Hill
      • Research: Tom’s research will use electronic health records and insurance claims to assess the impact of free school meal policies on children’s mental health and paid family leave on parent mental health.
    •  Fellow: Liz Nova
      • Department: Sociology
      • Adviser: Zack Almquist/Nathalie Williams
      • Research: Liz’s work will focus on how individuals access information about health and healthcare from sources outside of healthcare settings, such as social media, and use this information to make decisions about elective healthcare procedures.
    • Fellow: Katie Paulson
      • Department: Biostatistics
      • Adviser: Jon Wakefield
      • Research: Katie’s research will revamp existing UN Inter-agency Group for Mortality Estimation Bayesian methods for estimation of national child mortality from census, vital registration and household survey data by incorporating survival methods.