Daniel Heitjan

Daniel Heitjan is Professor and Chair of the Department of Statistical Science at Southern Methodist University (SMU) and Professor of Biostatistics in the O'Donnell School of Public Health at UT Southwestern Medical Center (UTSW). He also directs the collaborative SMU/UTSW PhD Program in Biostatistics, bridging academic and medical research. His career includes faculty positions at UCLA, Penn State, Columbia, and the University of Pennsylvania prior to his move to Texas in 2014.

He received a BSc in Mathematics (1981), an MSc in Statistics (1984), and a PhD in Statistics (1985), all from the University of Chicago. His academic journey reflects a deep commitment to statistical theory and its medical applications.

His research centers on methodological challenges in biostatistics, including clinical trial design, causal inference, and modeling with incomplete data. He has made significant contributions to statistical methods in health economics, pharmacogenomics, and smoking cessation. His work often addresses nonignorable missingness, sensitivity analysis, and real-time prediction in trials. He has developed tools like the R package isni to assess the impact of nonignorable coarsening, demonstrating both theoretical and practical innovation.

His 15 most recent publications reveal a consistent focus on improving the validity and efficiency of clinical and observational studies. Topics span from dose-escalation designs in oncology to cost-effectiveness analysis with unmeasured confounders, and from cure modeling to handling heaped self-reports. These works collectively emphasize robust inference under complex data conditions, particularly in public health and medicine.

While no specific awards are listed, his extensive publication record in top journals such as Biometrics, Statistics in Medicine, and Annals of Statistics indicates significant recognition in the field.

He has advised or collaborated closely with several researchers, including Y. Li, H. Xie, and G.-S. Ying, suggesting an active role in mentoring graduate students and postdoctoral fellows. His work is supported by interdisciplinary collaborations, especially with medical researchers at UTSW. He has also contributed to statistical software development and methodological guidelines in pharmacometrics.

Daniel Heitjan leads a research program that integrates advanced statistical theory with real-world health applications, particularly in cancer, smoking cessation, and health policy. His dual affiliation with SMU and UTSW enables a unique synergy between academic statistics and clinical research.