Advancing the science of causal inference and its application to business and policy problems.
The Wharton Causal Data Science Lab (WCDSL) develops methods to identify cause-and-effect relationships in complex real-world settings. From business strategy to public policy, our research helps decision-makers move beyond correlation and act on evidence that matters.
Get Involved
STUDENT OPPORTUNITIES
The Lab is committed to creating meaningful opportunities for students to engage with real-world data science and policy challenges.
Community Data Science: STAT 9915 (Launching Fall 2025)
This course provides students with the opportunity to hone their data science skills and gain practical experience by working with a Philadelphia-based community organization on a data science problem of interest to the organization. Students will work in groups on a data science problem of interest to a community organization. Students will gain skills in problem formulation, collaboration with community organizations and communication of data science results. Learn More »
Summer Research Experience
Each summer, the lab will offer a mentored research opportunity for at least one undergraduate student interested in pursuing a PhD in statistics or data science. Students will gain experience with applied research, contribute to active lab projects, and explore pathways in academic and professional data science.
INDUSTRY PARTNERSHIPS
The Lab collaborates with industry leaders, nonprofits, and government agencies to address high-impact challenges through the science of causal inference. We focus on creating actionable insights that drive smarter decisions in business strategy and public policy.
Our projects prioritize real-world relevance and social impact—with particular attention to initiatives that support the greater Philadelphia region. Whenever possible, Wharton undergraduates are engaged as research assistants, gaining hands-on experience in applied analytics and policy-relevant work.
Partner with Us
We welcome partnerships with companies seeking to apply cutting-edge causal data science to real-world problems. Learn more about partnership opportunities through the Wharton AI & Analytics Initiative Engagement Opportunities.
Research
We apply causal inference methods to understand complex policy and business problems.
Here are a few examples of our recent work.
BACKGROUND CHECK LAWS AND GUN HOMICIDES
HAVING A GUN AT HOME AND SUICIDE RISK
LONG TERM EFFECTS OF YOUTH SPORTS PARTICIPATION
Adolescent Sports Participation and Health in Early Adulthood: An Observational Study
Featured Media
High school football isn’t linked to brain problems later on — if you played in the 1950s
There’s no end to headlines about the dangers of head injuries in football. But a new study suggests that high school football, at least, was not associated with cognitive problems — like having trouble remembering words or letters — later in life.
The new study isn’t the last word on the dangers of football, especially for kids, but it shows that more research needs to be done.
Meet Our Team
Dylan Small
Universal Furniture Professor; Professor of Statistics and Data Science, Department of Statistics and Data Science, The Wharton School
Dr. Small’s research interests include causal inference, design, and analysis of experiments and observational studies for comparing treatments, longitudinal data, measurement error, and applications of statistics to health and public policy. He is currently the co-editor of the Journal of the American Statistical Association and was the founding editor of Observational Studies. He was the 2024 president of the Society for Causal Inference. He co-founded the Wharton Masters of Arts in Statistics and Data Sciences, Bridge to a Doctorate program https://statistics.wharton.upenn.edu/programs/bridge/
Dr. Small received his PhD in Statistics from Stanford University.
Universal Furniture Professor
Professor of Statistics and Data Science
Faculty Lead, Wharton Causal Data Science Lab
dsmall@wharton.upenn.edu
Will Bekerman
PhD Student
Abhinandan Dalal
PhD Student
Yu Gui
Postdoctoral Fellow
Iris Horng
PhD Student
Jonathan Pipping
PhD Student
Matthew Spivey
Undergraduate Researcher
Albert Zeng
Undergraduate Researcher
Zhong Zheng
Postdoctoral Fellow
Contact
Wharton Causal Data Science Lab
417 Academic Research Building
265 South 37th Street
Philadelphia, PA 19104
ai-analytics@wharton.upenn.edu