Our main research interest is in developing statistical methods and machine learning tools for cutting-edge bio-technologies and genetic problems. We currently work on various problems related to single-cell multi-omics and Mendelian Randomization. We also develop new statistical methods and theory for multiple p-values combination to increasing replicability and/or power, causal inference and factor models, with their applications in statistical genetics.