Date: Tuesday, September 30, 2025 12-1pm ET
The Committee of Presidents of Statistical Science (COPSS), in collaboration with the National Institute of Statistical Sciences (NISS), hosted a Leadership Webinar titled “Statistical Leadership for AI-Enabled Health.” The event emphasized the essential role of statisticians in guiding interdisciplinary research and innovation at the intersection of statistics, data science, artificial intelligence, and health. The webinar featured two distinguished leaders in the field: Dr. Hongtu Zhu, Kenan Distinguished Professor of Biostatistics, Statistics, Radiology, Computer Science, and Genetics at the University of North Carolina at Chapel Hill, and Dr. Xihong Lin, Professor and Chair of the Department of Statistics at Harvard University. Both shared insights from their unique leadership journeys and offered guidance on advancing research and influence in complex scientific environments.
Leadership Journey: Dr. Xihong Lin
Dr. Lin recounted her career trajectory, beginning with a decade at the University of Michigan, where she progressed from assistant to full professor while focusing on longitudinal data analysis. After moving to Harvard in 2005, she shifted her focus to genomics, including genome-wide association and whole-genome sequencing studies. She emphasized the importance of learning new domains from the ground up—auditing a molecular biology course to acquire foundational genetics knowledge enabled her to identify high-impact problems, communicate effectively with collaborators, and establish a niche for meaningful contributions. Dr. Lin also highlighted the value of scientific and administrative leadership, including guiding large research consortia, mentoring junior faculty, and fostering environments that support innovation.
Leadership Journey: Dr. Hongtu Zhu
Dr. Zhu described his path, which blends academic and industry experience. Beginning with a PhD in latent variable models, he gained experience in neuroimaging and statistical applications at Columbia University while collaborating with psychiatrists and computer scientists. Moving to UNC provided a unique opportunity to focus on medical imaging, biomedical research, and mentoring students. Dr. Zhu also engaged in large-scale projects such as the UK Biobank and cancer genomics consortia. He emphasized the importance of community-building and leadership beyond research, founding the ASA Statistical Imaging Section, organizing computational neuroscience programs, and hosting workshops that foster collaboration, mentorship, and shared learning.
Moderated Q&A: Key Themes of the Discussion
Moderated by Dr. Yize Zhao, Associate Professor in the Department of Biostatistics at Yale School of Public Health, the webinar focused on three central themes in statistical leadership: how to frame/proritize high-impact problems and set research visions; how to build cross-disciplinary teams and show statistical leadership; and perspectives on emerging research directions at the statistics-data science –AI interface.
During the moderated Q&A session, leading experts in statistical science and health research shared their insights on career development, research strategy, and emerging opportunities at the intersection of statistics and artificial intelligence (AI). Dr. Xihong Lin and Dr. Hongtu Zhu discussed key lessons from their careers and offered guidance for the next generation of statisticians and data scientists.
Investing in a Career
Dr. Lin emphasized the importance of mentorship and professional growth. “Watching students evolve from novices into prominent contributors in the scientific community has been immensely rewarding,” she noted. She also reflected on her 2008 sabbatical, during which auditing a molecular biology course enabled her to pivot into statistical genetics and genomics. Dr. Lin added that in hindsight, dedicating time to computer science in a more recent sabbatical would have further strengthened her ability to collaborate at the interface of statistics and AI.
Dr. Zhu highlighted the value of exploring new data types, beginning with neuroimaging and expanding into genomics, genetics, and electronic health record data. He emphasized learning how to process these datasets and the importance of collaboration with graduate students and colleagues, noting that much progress in his research was driven by their expertise. Engagement with interdisciplinary peers and attendance at key conferences, such as EPAMI, has also expanded his professional network and enhanced his understanding of computational infrastructure.
Choosing Research Problems Under Constraints
Dr. Lin advised that identifying high-impact research problems often involves exploring areas with few active researchers but significant potential. She cited examples from her own work, including early engagement in rare variant analysis in whole-genome sequencing and integrating synthetic data into statistical methods, which positioned her lab to access large-scale datasets and pioneer methodologies bridging statistics and AI.
Dr. Zhu recommended beginning with real-world data to understand pressing biomedical problems and iteratively improving methods. He underscored the importance of writing grants and leveraging collaborations to pool expertise and datasets. Participation in initiatives such as the DREAM Challenges, he added, allows students to develop practical skills and benchmark their work against peers.
Leadership in Interdisciplinary Teams
Dr. Lin advised statisticians to aim to be recognized as domain scientists rather than solely as statistical collaborators. Developing expertise in the scientific domain allows statisticians to identify critical problems, communicate effectively, and make meaningful contributions to large consortia. She highlighted her involvement in high-profile NIH consortia, noting that leadership in analytics and data management amplifies scientific impact.
Dr. Zhu emphasized that leadership begins with strong collaboration, helping others achieve their goals while demonstrating value. He encouraged statisticians to develop deep knowledge of the datasets and problems they address, moving from supporting roles to leading research initiatives by identifying high-impact questions in biomedical science.
Emerging Opportunities in Statistics and AI for Health
Dr. Lin underscored the high standards required in health research due to its direct impact on human lives. She described a two-way integration of AI and statistics: leveraging generative AI, such as synthetic data, to enhance statistical inference, and applying rigorous statistical principles to AI outputs to quantify uncertainty and improve reliability, including the generation of confidence measures for large language model outputs.
Dr. Zhu advocated for “end-to-end” research, where statisticians address meaningful problems throughout all stages of the research lifecycle—from raw data processing and study design to data integration and methodological development. This comprehensive approach ensures that contributions are both significant and applicable.
The discussion provided a roadmap for aspiring statisticians and data scientists seeking to navigate the evolving landscape of health research and AI, emphasizing mentorship, strategic problem selection, interdisciplinary collaboration, and methodological rigor.
Thank You & Acknowledgements
The Committee of Presidents of Statistical Science (COPSS) and the National Institute of Statistical Sciences (NISS) extend sincere gratitude to Dr. Xihong Lin and Dr. Hongtu Zhu for sharing their invaluable insights and experiences. Their perspectives on career development, research strategy, and leadership in statistical AI for health provided a rich resource for the statistical and data science community. We also thank Dr. Yize Zhao for expertly moderating the discussion, highlighting actionable lessons for early-career and established statisticians alike.
NISS extends sincere gratitude to COPSS for organizing this Leadership Webinar and supporting the advancement of statistical leadership in AI-enabled health. Finally, we acknowledge all attendees, whose engagement through questions and discussion helped make the webinar a dynamic forum for learning, mentorship, and community building, advancing the dialogue on interdisciplinary collaboration and the future of AI-enabled health research.
About the COPSS-NISS Leadership Webinar Series
COPSS (Committee of the Presidents of Statistical Societies) and NISS have come together to organize and host a new webinar series focusing on leadership in statistics and data science. Plan to attend these webinars every month during the academic year! Visit the COPSS-NISS Leadership Series Page for previous webinars.
The COPSS-NISS Leadership Webinar Series is co-organized by the Committee of the Presidents of Statistical Societies (COPSS) Emerging Leaders in Statistics and the National Institute of Statistical Sciences (NISS). The purpose of the webinar series is to promote leadership skills for members of the statistical societies at any stage in their careers. The series features conversations with leaders throughout the discipline, including leaders from major academic and government institutions, and companies. Invited speakers share their leadership stories and answer questions about their experiences. Each webinar is moderated by a member of the COPSS Emerging Leaders in Statistics program.
Access the Full COPSS-NISS Leadership Webinar Series YouTube Playlist | COPSS-NISS Leadership Webinar Series: https://www.youtube.com/playlist?list=PLoRtupvDJTjvFukMcO6NfDr0GvxDsIj81