data science

SPH Launches New Center for Health Data Science

Debbie Cheng, professor of biostatistics, will lead the new center, which will combine and expand the work of the Population Health Data Science Program and the Biostatistics and Epidemiology Data Analytics Center.

The School of Public Health has launched a new Center for Health Data Science to advance scholarship in one of the most dynamic and promising areas of public health research.

Debbie Cheng, professor of biostatistics, will be the inaugural executive director of the center, which will combine and build on the innovative interdisciplinary work of the Population Health Data Science (PHDS) Program and the Biostatistics and Epidemiology Data Analytics Center (BEDAC). 

“My vision for the new center is simple: Data Science for the Health of All,” Cheng says. “Our mission is to integrate high-quality data science into the core pillars of our school’s purpose to Think, Teach, and Do.”

Cheng, who will also assume the newly created role of assistant dean of data science at SPH, aims to “foster new research synergies across multiple disciplines engaged in health data science.”  She envisions expanding the activities of the Population Health Data Science Program—which include seminars, workshops, and seed funding opportunities—to help strengthen connections with health data scientists and to catalyze innovative health research.

Through BEDAC, a long-standing and indispensible resource for investigators, Cheng plans to continue providing a comprehensive range of high-quality data management and statistical analysis services, both across the University and with external partners in academia, government, foundations, and industry. She also envisions the new center as a hub for training and continuing-education opportunities, serving as a bridge that connects students with faculty and staff for mentored projects.

Building on her efforts leading the PHDS Program, Cheng will continue to facilitate collaborations with colleagues across the University, including the Hariri Institute for Computing and Computational Science & Engineering, the Faculty of Computing & Data Sciences, the College of Engineering, as well as key groups on the medical campus, such as Computational Biomedicine, the Clinical and Translational Institute (BU CTSI), the Evans Center for Interdisciplinary Biomedical Research, and BMC investigators.

Cheng expresses her enthusiasm for fostering further interdisciplinary partnerships and collaborations, adding, “I believe that by enhancing our team science and academic programs, we can elevate the overall quality of health research, ultimately generating important new knowledge and advancing population health.”

In a message to the SPH community announcing the new center, Dean Sandro Galea hailed Cheng as “a distinguished member of the SPH community, contributing much to the field of biostatistics and to the life of our school.”  In addition to her duties at PHDS, she seves as director of the Biostatistics and Data Management Core for the International URBAN ARCH Center, associate director for the Providence/Boston Center for AIDS Research (CFAR) and co-director of its Biostatistics Core.

Her research is primarily centered on applied statistics, particularly in the analysis of longitudinal data, and the design and analysis of clinical trials. Cheng is the lead statistician for the Massachusetts site of the HEALing Communities Study, a multi-site cluster randomized trial aimed at reducing opioid-related overdose deaths in communities across four different states, the largest study of its kind in addiction science. Cheng is a fellow of the American Statistical Association.

Cheng is the lead author of a recent a New England Journal of Medicine “Perspectives” article titled “The Sense and Sensibility of Sensitivity Analyses.” In this piece, Cheng and co-author Joseph Hogan of Brown University discuss the critical role of sensitivity analyses in assessing the robustness of trial findings. .  They emphasize that advance planning and pre-specification are vitally important to ensure sensitivity analyses are properly conducted and accurately reported.