Speaker
Dr. Peter X. K. Song, Professor of Biostatistics, School of Public Health, University of Michigan, Fellow of IMS, ASA, and Member of ISI
Title
Plenary Talk at American Statistical Association AL-MS Chapter Annual Conference
Subtitle
Statistical Approaches to Addressing Data Science Challenges in Epigenetic Aging Research
Physical Location
Fowlkes Auditorium in Colvard Student Union
Time: TBA
Abstract:
DNA methylation (DNAm) has emerged as a key source of omics data for assessing biological age, offering a wealth of genetic markers that reflect cellular changes influenced by social and environmental factors. Epigenetic age can be estimated through predictive models known as epigenetic clocks, which rely on high-dimensional data analytics. However, current epigenetic age calculators face significant limitations as DNAm data collection technology rapidly advances. In this talk, I will present statistical approaches to tackle several critical challenges, including: (i) refining epigenetic clocks with higher-resolution DNAm data using convolutional neural networks, (ii) quantifying prediction uncertainty using conformal prediction techniques, and (iii) leveraging transfer learning to shift from mean to quantile predictions. This presentation will integrate both statistical methodologies and algorithmic solutions, demonstrated through real-world data applications.
About the Speaker:
Dr. Song is Professor of Biostatistics at the School of Public Health in the University of Michigan, Ann Arbor. He received his PhD in Statistics from the University of British Columbia, Vancouver, Canada in 1996. He has published over 230 peer-reviewed papers and graduated 26 PhD students and trained 6 postdoc research fellows. Dr. Song’s current research interests include data integration, distributed inference, high-dimensional data analysis, longitudinal data analysis, mediation analysis, spatiotemporal modeling, and applications in medicine and public health. He collaborates extensively with researchers from nutritional sciences, environmental health sciences, chronic diseases, infectious disease, aging and nephrology. He is IMS Fellow, ASA Fellow and Elected Member of the International Statistical Institute. Dr. Song now serves as Editor of the Annals of Applied Statistics and Associate Editor of the Journal of American Statistical Association and the Journal of Multivariate Analysis.