COPSS-NISS Leadership Webinar: Statistical Leadership for AI-Enabled Health

Overview

AI is reshaping statistics, health, and medicine. This COPSS–NISS Leadership Webinar features Dr. Xihong Lin and Dr. Hongtu Zhu on how statistical leadership drives AI-enabled precision health—from framing high-impact problems to integrating multimodal data and building scalable, trustworthy models. They will share practical approaches to setting research vision, prioritizing projects with real-world impact, and building effective cross-disciplinary teams, with emphasis on reproducibility, fairness, and translating methods into clinical and public-health value. The speakers will also offer perspectives on emerging research directions at the statistics–data science–AI interface and provide guidance for shaping a meaningful career and leadership path in the profession.

Speakers

Hongtu Zhu, Kenan Distinguished Professor, Department of Biostatistics at University of North Carolina & Columbia University and New York State Psychiatric Institute

Dr. Xihong Lin, Professor and Chair of the Department of Statistics Department of Statistics, Harvard University

Moderator

Dr. Yize Zhao, Associate Professor, Department of Biostatistics, YSPH, Yale University

About the Speakers

Dr. Hongtu Zhu is a professor in the Department of Biostatistics. He has a broad background in statistics, biostatistics, medical imaging, genetics and computational neuroscience, with specific training and expertise in neuroimaging data analysis and big data integration as well as secondary data analysis on neurodegenerative and neuropsychiatric diseases. As a graduate student and postdoctoral fellow, he developed various new statistical methods for analyzing genetic, behavioral and clinical data from cross-sectional, longitudinal and family studies, and solved associated statistical issues (e.g., estimation, hypothesis testing). As a faculty member at Columbia University and New York State Psychiatric Institute, he expanded his research to develop new statistical methods for the analysis of medical imaging data including magnetic resonance images (MRI), DTI, EEG/MEG, Ultra Sound, fMRI and PET. See Profile

Dr. Xihong Lin is Professor and Former Chair of the Department of Biostatistics, Coordinating Director of the Program in Quantitative Genomics at the Harvard T. H. Chan School of Public Health, and Professor and Chair of the Department of Statistics in the Faculty of Arts and Sciences at Harvard University, and Associate Member of the Broad Institute of MIT and Harvard. Dr. Lin’s research interests lie in the development and application of scalable statistical and machine learning/AI methods for the analysis of massive and complex genetic and genomic, epidemiological and health data. Dr. Lin was elected to the National Academy of Medicine in 2018 and the National Academy of Sciences in 2023. She received the 2002 Mortimer Spiegelman Award from the American Public Health Association, the 2006 Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award, the 2017 COPSS FN David Award, the 2008 Janet L. Norwood Award for Outstanding Achievement of a Woman in Statistics, the 2022 National Institute of Statistical Sciences Jerome Sacks Award for Outstanding Cross-Disciplinary Research, and the 2022 Marvin Zelen Leadership in Statistical Science Award. She is an elected fellow of American Statistical Association (ASA), Institute of Mathematical Statistics, International Statistical Institute, and the American Association of the Advancement of Sciences (AAAS). Dr. Lin is the former Chair of the Committee of Presidents of Statistical Societies (COPSS) (2010-2012) and a former member of the Committee of Applied and Theoretical Statistics (CATS) of the National Academy of Science. She is the founding chair of the US Biostatistics Department Chair Group, and the founding chair of the Young Researcher Workshop of East-North American Region (ENAR) of the International Biometric Society. She co-launched the Section of Statistical Genetics and Genomics of the American Statistical Association and served as a former section chair. She is the former Coordinating Editor of Biometrics and the founding co-editor of Statistics in Biosciences. She has served on a large number of committees of many statistical societies, numerous NIH and NSF review panels, and several committees of National Academies. See Profile

About the Moderator

Dr. Yize Zhao is an Associate Professor in the Department of Biostatistics at Yale School of Public Health. She is also affiliated with Yale Department of Biomedical Informatics & Data Science, Yale Center for Analytical Sciences, Yale Alzheimer's Disease Research Center, Yale Wu Tsai Institute, Yale Center for Brain and Mind Health, and Yale Computational Biology and Bioinformatics. Her main research focuses on the development of statistical and AI methods to analyze large-scale complex data (medical imaging, -omics, EHRs), Bayesian methods, feature selection, predictive modeling, data integration, missing data and network analysis. She has strong interests in biomedical research areas including mental health, psychiatry, neurodegenerative diseases, and aging. Her most recent research agenda includes analytical method development and cutting-edge scientific applications on brain-to-behavior modeling, multi-layer biomedical networks, imaging genetics and genomics, and the integration of multi-modal biomedical data with real-world data (EHRs, video, audio, etc.). Her research is supported by multiple NIH grants. Dr. Zhao is the recipient of the prestige Thelma and Marvin Zelen Emerging Women Leaders in Data Science Award from the Institute of Mathematical Statistics (IMS), and the COPSS Emerging Leader Award from the Committee of Presidents of Statistical Societies (COPSS). She is currently a standing member of the NIH Biodata Management and Analysis (BDMA) study section. See Profile

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