Graduate Profile: Q&A with Denys Shay
Name: Denys Shay
Area of Research: Clinical Epidemiology
Degree: PhD
Year of Graduation: 2026
Current Role: Associate, Analysis Group, Inc.
- What did you do before pursuing your graduate degree?
Before coming to Harvard for my PhD, I worked as a Research Associate in the Department of Anesthesia, Critical Care and Pain Medicine at Beth Israel Deaconess Medical Center. Using electronic health record data, I studied the effectiveness and safety of treatments in perioperative and intensive care settings, with the goal of identifying opportunities to improve patient outcomes. Before moving to Boston, I earned my medical degree from Charité – Universitätsmedizin Berlin in Germany. My medical training shaped the questions I wanted to study, while my research experience showed me that answering those questions rigorously required deeper training in epidemiology and biostatistics. - What attracted you to the program at Harvard?
Harvard offered a combination that was difficult to find elsewhere: rigorous methodological training, a dedicated focus on clinical epidemiology, and close connections to an extraordinary clinical research environment. The Harvard Chan School is located in the heart of the Longwood Medical Area, surrounded by major teaching hospitals and research institutions. This creates opportunities to pursue clinically meaningful questions while learning from investigators who have helped shape many of the epidemiologic and causal inference methods used throughout medical research today. Since I had already established a network of collaborators in Boston, the opportunity to strengthen those relationships while joining a PhD program with an explicit focus on clinical epidemiology made Harvard a natural choice for me. - What surprised you the most about being a graduate student in your chosen research program?
I was surprised by how quickly the field of observational clinical research evolved during my time in the program. The target trial emulation framework, which has been advanced by researchers at Harvard Chan, became increasingly influential in how investigators approach causal questions using observational data. I also saw a broader shift in how so-called “real-world evidence” is evaluated and communicated. Causal language and modern causal inference methods have become more widely accepted in leading medical journals and increasingly relevant to regulators and other health care decision-makers. It has been exciting to train in an environment that is not simply teaching established methods, but actively shaping the methodological standards for evidence generation. - Why do you think your research area is important to public health?
Clinicians, patients, regulators, and policymakers often need to make decisions when evidence from randomized trials is incomplete or unavailable. Trials may not include all relevant patient populations, may have limited follow-up, or may not directly compare the treatments used in routine clinical practice. Clinical epidemiology can help address these evidence gaps. By applying rigorous study designs and analytical methods to real-world data such as electronic health records and insurance claims, researchers can evaluate the effectiveness and safety of treatments in broader and more representative populations. This work can inform clinical guidelines, regulatory decisions, and also conversations between clinicians and patients. Ultimately, the goal is to translate data collected during routine care into reliable evidence that improves health outcomes. - What suggestions would you have for someone interested in applying for this research area?
This is an especially exciting time to enter clinical epidemiology. The volume and diversity of health data available for research continue to grow, while the data themselves are becoming increasingly standardized and accessible. Emerging technologies, including ambient AI, may further expand the range and quality of clinical information available for research. At the same time, more data do not automatically lead to better evidence. The field needs well-trained clinical epidemiologists who understand study design, causal inference, biostatistics, clinical medicine, and the limitations of real-world data. I would therefore encourage prospective students to build a strong quantitative foundation, develop a thoughtful understanding of how clinical data are generated and used, and use the PhD program to refine these skills while pursuing research with mentorship from leading epidemiologists. - How has your time in the program influenced your career path?
The program showed me that improving health can take many forms, including work that extends beyond the one-on-one interactions in clinical practice and influences care at the population level. It broadened my perspective on how research can shape clinical decisions, treatment development, regulatory decision-making, health policy, and standards of care. The program also gave me the training in epidemiology, biostatistics, causal inference, and real-world evidence needed to contribute to this work. Most importantly, I learned how to translate clinically important questions into rigorous studies that can generate evidence relevant to entire patient populations. That perspective has strongly shaped the kind of work I hope to pursue in my career. - Is there anything else that you would like to share about your experience at the Harvard Chan School?
One of Harvard Chan’s greatest strengths is the breadth of expertise across the School and the wider Harvard community. Whether your interests center on a particular disease, data source, study design, or methodological challenge, you are likely to find someone working at the forefront of that area. The research community is also highly collaborative. Faculty members, postdocs, and fellow students are generous with their time and willing to discuss ideas, offer thoughtful feedback, and connect you with collaborators who can help move a project forward. This combination of research excellence and a supportive academic environment has made my experience at the Harvard Chan School particularly valuable.
