Organizers

Karen N. Conneely, PhD is a Professor of Human Genetics at Emory University whose research focuses on statistical genetics, genetic epidemiology, and the integration of genomic and epigenomic data to understand complex human diseases. She earned her PhD from the University of Michigan in 2008, where she was a trainee in the Genome Science Training Program under Professor Michael Boehnke, who also chaired her doctoral committee. Dr. Conneely’s work spans methodological development for genome-wide and epigenome-wide association studies, analysis of gene–environment interactions, and studies of cardiometabolic and psychiatric traits. Through her leadership in collaborative research and training, she has advanced quantitative approaches for analyzing high-dimensional genomic data and contributed to the continued growth of statistical genetics.

Michael P. Epstein, PhD is a Professor of Human Genetics at Emory University whose research focuses on statistical methods for genetic epidemiology and the analysis of complex human diseases. He earned his PhD at the University of Michigan in 2002, where he was a trainee in the Genome Science Training Program and completed his doctoral work with Professor Michael Boehnke serving as co-chair of his dissertation committee. Dr. Epstein’s work has advanced methodological approaches for linkage and association studies, gene–gene and gene–environment interaction analysis, and the genetic dissection of complex traits. Through his leadership in collaborative research and training, he has contributed to the continued development of statistical genetics and genomic medicine.

Elizabeth R. (Beth) Hauser, PhD is a Professor in the Department of Biostatistics and Bioinformatics at Duke University School of Medicine, where her research focuses on statistical genetics and the genetic epidemiology of complex diseases, particularly cardiovascular and autoimmune disorders. She earned her PhD from the University of Michigan in 1998, with Professor Michael Boehnke serving as Chair of her doctoral committee. Dr. Hauser has played key roles in large-scale genetic studies, including genome-wide association and sequencing analyses aimed at identifying genetic contributors to complex traits. Through her methodological work and leadership in collaborative consortia, she has advanced understanding of the genetic architecture of multifactorial diseases and helped train the next generation of quantitative geneticists.

Mingyao Li, PhD is a Professor of Biostatistics at the University of Pennsylvania, where she develops statistical and computational methods for the analysis of high-dimensional genomic and transcriptomic data. She earned her PhD from the University of Michigan in 2005, with Professor Michael Boehnke serving as co-chair of her doctoral committee, and went on to build a research program at the intersection of statistical genetics, functional genomics, and cancer genomics. Dr. Li’s work spans gene expression analysis, eQTL mapping, integrative multi-omics methods, and the study of genetic and molecular mechanisms underlying complex diseases. Through leadership in collaborative genomic consortia and methodological innovation, she has advanced tools that translate large-scale genomic data into biological insight.

Yun Li, PhD is a Professor of Genetics and Biostatistics at the University of North Carolina at Chapel Hill, where her research focuses on the development and application of statistical methods and computational tools to the genetic dissection of complex human diseases and traits. With Michael Boehnke serving as co-chair of her doctoral committee, Dr. Li earned her doctoral degree in biostatistics from the University of Michigan in 2009, after which she joined the UNC faculty and has since led work on genotype imputation, rare-variant association analysis, local ancestry inference, and sequence-based study design — including contributions to the 1000 Genomes Project and large-scale sequencing studies of metabolic, cardiovascular, and neuropsychiatric traits. Her lab also develops methods for integrating multi-omics and chromatin interaction data to enhance interpretation of genome-wide association results, and she plays leadership roles in several multi-site consortia that advance statistical genetics and genomic analysis.

Kathryn L. Lunetta, PhD is a Professor of Biostatistics at the Boston University School of Public Health, where her research focuses on statistical genetics and the genetic epidemiology of complex diseases, including cardiovascular, pulmonary, neurologic, and aging-related traits. She earned her PhD from the University of Michigan in 1996, with Professor Michael Boehnke serving as Chair of her doctoral committee. Dr. Lunetta has contributed extensively to large-scale genome-wide association and sequencing studies through major collaborative consortia, including work within long-standing cohort studies such as the Framingham Heart Study. Her methodological and applied research has helped advance understanding of genetic risk factors across diverse populations and complex phenotypes.

Sebastian Zöllner, PhD is a Professor of Biostatistics at the University of Michigan and a core faculty member of the Center for Statistical Genetics. A long-time colleague and collaborator of Professor Michael Boehnke, Dr. Zöllner has played a central role in advancing statistical methods for genetic mapping, rare variant analysis, and population genetics. He has been deeply involved in the Genome Science Training Program, mentoring trainees and helping shape interdisciplinary education at the interface of genetics and quantitative science. His research integrates methodological innovation with large-scale genomic studies to improve understanding of the genetic architecture of complex human diseases, strengthening Michigan’s longstanding leadership in statistical genetics.

Veera Baladandayuthapani, PhD is Professor and Chair of Biostatistics at the University of Michigan School of Public Health and a core faculty member of both the Center for Statistical Genetics and the Genome Science Training Program. A colleague of Professor Michael Boehnke, he develops innovative Bayesian and machine learning methods for high-dimensional genomic and multi-omics data, with particular applications in cancer genomics and precision medicine. His research spans Bayesian hierarchical modeling, functional data analysis, and integrative approaches for complex biological systems. Through methodological innovation, interdisciplinary collaboration, and training leadership, Dr. Baladandayuthapani contributes to Michigan’s continued strength in statistical genetics and quantitative biomedical research.