Douglas Landsittel didn’t give a second thought to applying to or enrolling at the University of Pittsburgh - a major research institution in his hometown with a strong math department and the exact type of large, urban setting that he sought for college.
Landsittel had already decided while he was in high school that he’d be pursuing mathematics in college, and so he earned his BS in applied mathematics in 1992. “I’ve always been drawn to math, but I wanted to work on problems with real-world impact,” he said.
It was during those undergraduate years that he focused that interest toward statistics. “I always joke that the reason I'm in statistics is because I'm terrible at physics,” he said. “After my first year, one of the decision points was should I stay in mathematics or go into applied math and I either needed to take a physics 3 course [for pure math] or a stats course [for applied],” he explained. From his experience in the second-level physics course, he thought he’d be better at statistics.
Taking a course with Frank D’Amico, then an adjunct faculty member at Pitt working at both Duquesne University and St. Margaret’s Hospital before it was in the UPMC system, got Landsittel thinking about statistical research as a career. “He had a way of making statistics intuitive,” Landsittel said of D’Amico. “His teaching helped me see how the field could be applied to medical research and public health and he was very good at intuitively explaining this idea of what do we mean when we say ‘research shows…?’ It was really fascinating to me and I thought, ‘I could do this for a living.’ "
From there, Landsittel decided to stay at Pitt and go directly into the established and well-reputed PhD program in biostatistics. With a national reputation for studies in cancer and occupational research, it was a natural choice. He completed his PhD in 1997 at the School of Public Health.
For his doctoral research, Landsittel worked with Richard Day on studies in ophthalmology and cancer research and with Vincent Arena on model selection in artificial neural networks, an area that was just gaining attention in the early 1990s. “We were looking at how to balance model complexity with predictive accuracy—questions that are still very relevant today,” he said. His dissertation led to several publications and laid the groundwork for his interest in computational methods in health research.
After graduation, Landsittel worked for the Centers for Disease Control and Prevention where he held positions including team leader, acting branch chief, senior statistician, and senior fellow across three different divisions including their National Institute for Occupational Safety and Health. “The CDC gave me a broader perspective on public health—from workplace safety to environmental exposures—and how to use data to inform national policy,” he said.
After the CDC, he came back to academia and his alma matter, working in a variety of leadership roles at Pitt. He served as associate director for the Biostatistics Facility of the Cancer Institute (now Hillman Cancer Center), associate director for the Center for Research on Healthcare Data Center, director of biostatistics for research at the Starzl Transplant Institute, and lead methodologist for the Comparative Effectiveness Research Center. “Each of these roles gave me a chance to work with clinicians and researchers from different fields,” he said. “That collaboration is essential to solving complex health problems. I’ve always been interested in mentoring and building programs, and these leadership roles gave me the opportunity to do that on a larger scale,” he said.
Later, Landsittel became chair of the Department of Epidemiology and Biostatistics and held the James A. Caplin, MD Chair in Evidence-Based Medicine at Indiana University–Bloomington. In February 2024, he joined the University at Buffalo as Chair of the Department of Biostatistics in the School of Public Health and Health Professions. His research has spanned several areas, including critical care, polycystic kidney disease, and large-scale observational studies. “One of the main challenges is designing studies that are rigorous but still feasible in real-world settings,” he said. “We have to meet researchers where they are and help them get the most out of their data.”
Landsittel’s approach emphasizes the role of statisticians as active participants in scientific discovery. “We need to be seen not just as data analysts, but as scientific collaborators who help shape research questions and study design,” he said.
In 2024, he was recognized with the Public Health Alumni Award for his contributions to public health and data science, a meaningful milestone. “It’s incredibly humbling,” Doug said. “It’s not just recognition of my work, but of the many teams and students I’ve been fortunate to work with over the years.”
Landsittel's connection to Pittsburgh remains strong. He remembers running around the city, exploring its neighborhoods, and enjoying local restaurants. “Pittsburgh was where I first saw how academic research could connect to community needs,” he said. “It shaped how I think about the role of public health.”
In addition to his academic work, he is committed to supporting underrepresented students in statistics, inspired by another of his mentors, former department chair Sally Morton. “Mentorship was key in my own journey, and I want to help create opportunities for students who might not otherwise consider this field,” he said. “Diversity in our field strengthens the quality of research and the relevance of our findings.”
“I received a solid foundation in both theory and application,” Landsittel reflected on his time at Pitt. “That balance has been critical in every stage of my career.” His advice for students is clear: “Follow your interests, seek good mentors, and don’t be afraid to step into roles that push you to grow.”
Today, he continues to mentor students and collaborate on research that bridges disciplines. His work is rooted in the belief that statistics can—and should—play a central role in improving public health. “The future of our field is in both statistical research and interdisciplinary teams, and I’m excited to be part of that progress.”
-Calvin Dziewulski