Panel session 1: Thursday, June 6 — 9 to 10 a.m.
Chair
Corinne Engelman
University of Wisconsin–Madison
Corinne Engelman is Population Health Science’s Vice Chair and Director of Graduate Programs. Her research focuses on the study design and data analysis of genetic, demographic, socioeconomic, behavioral, physiological and environmental factors of complex diseases, especially biomarkers and preclinical traits related to Alzheimer’s disease. Dr. Engelman’s group uses epidemiological, statistical, and bioinformatic approaches.
Panelists
Jiacheng Miao
University of Wisconsin-Madison
Jiacheng Miao is a PhD student in Biomedical Data Science at the University of Wisconsin–Madison. He studies problems at the intersection of human genetics, statistics, machine learning, and their application to medicine. Specifically, he has developed methods for applying machine learning to science while ensuring the validity of scientific discoveries, and approaches for estimating heterogeneous treatment effects and gene-environment interactions. He is a recipient of the distinguished student paper award from the American Statistical Association Section on Statistical Genomics and Genetics.
Presentation or paper
Valid inference for machine learning-assisted GWAS
Dhruva Jaishankar
Social Science Genetic Association Consortium
Jaishankar has a Master’s degree in Economics from the London School of Economics. He is currently working as a predoctoral research assistant at UCLA with the SSGAC.
Presentation or paper
Genomic-Relatedness Matched Association Studies Increase Diversity, Reduce Bias, and Increase Power Relative to GWAS
Yuchang Wu
University of Wisconsin-Madison
Yuchang Wu is an Assistant Scientist in the Biostatistics and Medical Informatics Department at University of Wisconsin-Madison working with Prof. Qiongshi Lu. His research interest is statistical analysis in human genetics.
Presentation or paper
Genomic-Relatedness Matched Association Studies Increase Diversity, Reduce Bias, and Increase Power Relative to GWAS