Dr. Li: I am an Associate Research Scientist with a background in viral dynamics and theoretical immunology. My interest is in bridging within-host immune response interactions with population-level viral transmission. With its collaborative environment and access to immersive, real-world datasets, the EMD Department provides the ideal setting to learn through hands-on analysis and advance my research.
EMD Associate Research Scientist Spotlight Series: Ke Li
Please tell us a little about yourself and what inspired you to pursue a Postdoc/Ph.D./MPH in the EMD Department at the Yale School of Public Health?
What is the current focus of your research?
Dr. Li: I focus on household transmission studies to understand how Respiratory Syncytial Virus (RSV) spreads across age groups and within close-contact settings. My current work involves developing statistical and mathematical tools for analyzing household transmission data and building an R package to facilitate these analyses for broader research use.
What are some of the most significant findings or innovations from your respiratory pathogens research?
Dr. Li: I have developed multiscale models linking individual viral kinetics to transmission risk that, in turn, help identify age-specific factors in RSV transmission and provide a framework for predicting who is most likely to transmit RSV that can then be targeted in prevention strategies.
Which emerging trends or technologies in respiratory pathogens research do you find most exciting?
Dr. Li: I’m most excited about the growing use of AI and machine learning to analyze complex epidemiologic datasets. These approaches are transforming how we detect patterns, forecast transmission, and integrate multiscale data. They offer new opportunities to understand and respond to respiratory pathogens.
Where do you see the field of respiratory pathogens research heading in the next few years, and what role do you hope your work will play in this future landscape?
Dr. Li: The field is moving toward integrated models that combine immunology, viral kinetics, and disease transmission data. I hope my work contributes to this multiscale understanding and helps develop more targeted interventions—especially for RSV and other pediatric respiratory pathogens.
How has the EMD Department supported your research and academic goals?
Dr. Li: The EMD Department provides exceptional mentorship, interdisciplinary collaboration, and access to high-quality data and computational resources. The department fosters an environment where quantitative researchers can thrive and supports both methodological development and practical public health impact.
What advice would you give to prospective students considering applying to the EMD training programs at Yale?
Dr. Li: Be curious, collaborative, and open to interdisciplinary approaches. The EMD Department offers incredible mentorship and flexibility, so take advantage of opportunities to work across labs, fields, and modeling domains. Engage early with faculty and pursue projects that genuinely excite you.