Loading…

Registration opens August 15th at www.idwsds.org.
Subject: 123 clear filter
arrow_back View All Dates
Tuesday, October 6
 

22:00 UTC

S123 - Borrowing Strength: Statistical Strategies for Imperfect Data
Tuesday October 6, 2026 22:00 - 23:00 UTC
This session highlights how modern biostatistics tackles a shared challenge across very different problems: making valid, efficient inference when the data we have is incomplete, limited, imbalanced, or imperfectly comparable to the question we want to answer. Talks in this session explore how statisticians "borrow strength" – from historical or external data sources, from related but heterogeneous datasets, from carefully constructed causal designs, and from generative models that learn the structure of missingness itself – to push beyond the limitations of any single dataset. Together, these four talks, spanning clinical trials, large-scale survey methodology, high-dimensional prediction, and observational causal inference, showcase the breadth of ideas at the intersection of biostatistics, machine learning, and causal reasoning, and the methodological creativity required to turn imperfect data into trustworthy conclusions.
Speakers
avatar for Xiaoting Chen

Xiaoting Chen

New York University
Xiaoting Chen is a 4th-year Biostatistics PhD candidate at New York University School of Global Public Health. Her research focuses on dynamic borrowing methods for clinical trial design, with an emphasis on frequentist frameworks that combine historical and concurrent control data... Read More →
avatar for Yuyu(Ruby) Chen

Yuyu(Ruby) Chen

New York University
Yuyu(Ruby) Chen recently graduated from NYU School of Global Public Health with PhD in Biostatistics. Her PhD work focused on developing and evaluating advanced missing data imputation frameworks tailored for healthcare research, which covers the aspects including clinical trials... Read More →
avatar for Jianan Zhu

Jianan Zhu

New York University
Jianan is a rising fifth-year PhD student in Biostatistics. Her main research interest is on design-based causal inference. She is interested in observational studies, randomized trials, sensitivity analysis, and their applications in health policy research, infectious disease research... Read More →
avatar for Iris Zhang

Iris Zhang

New York University
Iris is a 4th-year Biostatistics PhD student at New York University School of Global Public Health. Her research focuses on statistical machine learning and high-dimensional inference, with an emphasis on transfer learning, representation learning, and AI-driven methods for healthcare... Read More →
Chairs/Hosts Organizers
avatar for Xiaoting Chen

Xiaoting Chen

New York University
Xiaoting Chen is a 4th-year Biostatistics PhD candidate at New York University School of Global Public Health. Her research focuses on dynamic borrowing methods for clinical trial design, with an emphasis on frequentist frameworks that combine historical and concurrent control data... Read More →
Tuesday October 6, 2026 22:00 - 23:00 UTC
Zoom Room #1
 
  • Filter By Date
  • Filter By Venue
  • Filter By Type
  • Country
  • Session ID
  • Timezone


Share Modal

Share this link via

Or copy link

Filter sessions
Apply filters to sessions.
Filtered by Date -