Unlocking insights from complex data to advance biomedical research and education and to improve population health.
The Division of Biostatistics develops and applies innovative designs and quantitative tools that extract knowledge from complex laboratory and clinical data. We promote sound statistical practice that fully leverages study results, fostering reproducibility and enabling accurate interpretation. This work plays a critical role within the Perelman School of Medicine and the broader biomedical research community.
In the data-rich world of biomedical research, biomedical data science plays a key role in knowledge discovery-to devise and validate new clinical strategies for managing and treating disease-and biostatistics is central to this enterprise.
As experts in inferential thinking, biostatisticians’ work enables the global scientific community to unlock new knowledge and population insights from sampled data. Our unique understanding of randomness and variability positions us to lead experimental design and build models that can account for design-induced systematic biases; handle structures inherent to complex data; adjust for multiplicities that could produce false discoveries; and rigorously assess causal inference for observational data.
Our research is inherently collaborative. We work across labs, divisions, and departments to promote sound experimental design, analytical procedures, and reproducible research to address complex biomedical challenges.
Deputy Director, Biostatistics
Professor of Biostatistics
Deputy Director, Biostatistics
Professor of Biostatistics
Associate Director, Biostatistics
Executive Assistant to Dr. Jeffrey Morris (Biostatistics)
Stay informed with the latest research findings, news, and events from our division.
Nandita Mitra, PhD has been awarded the Lindback Foundation Award for Distinguished Teaching.
Dr. Eric Tchetgen Tchetgen has been awarded the inaugural David Cox Medal for Statistics, which honors mid-career researchers for outstanding contributions to the field.
In a new study, Yong Chen, PhD and colleagues at Penn Medicine, used AI and latent transfer learning to analyze long-COVID data, identifying four patient sub-populations with distinct care needs, improving hospital resource allocation and tailoring treatment for diverse patient populations.
Mingyao Li, PhD and her Penn Medicine colleagues developed an AI-powered tool called MISO (Multi-modal Spatial Omics) that can detect cell-level characteristics of cancer by looking at data from extremely small pieces of tissue—some as small as the width of five human hairs.
Associate Professor of Biostatistics
Alisa Stephens Shields, PhD, Associate Professor of Biostatistics, is recognized for her collaboration and impactful leadership in the realms of health, statistical education, and inclusion in the field. Her research focuses on extensions and innovative applications of causal inference approaches to enhance the design and analysis of clinical trials, as well as the development of patient-reported outcomes to inform population-appropriate trial endpoints. In this Q&A, Dr. Stephens Shields touches on her experiences in the DBEI research community, advice for students and early-career biostatisticians, and her recent 2024 Myrto Lefkopoulou Distinguished Lectureship from Harvard University.
Read Q&ABiostatistics research at Penn Medicine provides the statistical methods and analytical tools necessary to facilitate cutting-edge biomedical research and improve patient care. Collaborating with Epidemiology and Informatics, we discover and validate insights from complex data to develop precision strategies for disease prevention, risk reduction, therapy design, and population health guidelines.
Join a community of experts and mission-driven professionals committed to shaping the future of biomedical and population health data research through collaboration and scientific excellence. Explore available faculty and staff positions in the Division of Biostatistics and the department.