As an Assistant Professor (tenure-track) in the Department of Biostatistics and affiliated member in Data Science Institute at Columbia University, Dr. Wenpin Hou specializes in the development of statistical machine learning methods. Her research addresses the complex challenges at the nexus of statistics and data science, particularly in the realms of single-cell genomics, epigenomics, and spatial transcriptomics. Her focus extends to mathematical modeling of gene regulatory networks, with the ultimate goal of elucidating gene regulatory mechanisms. Dr. Hou has a keen interest in devising methodologies for analyzing spatio-temporal patterns within single-cell and spatial genomics and epigenomics data. Furthermore, she is an active researcher in applying Generative Pre-trained Transformer models for genomics. Dr. Hou’s collaborative efforts span a wide range of fields including cancer, immunology, infectious diseases, developmental processes, obesity, maternal and child health, and the ENCODE4 consortium. Her research is poised to unravel the intricate mechanisms underlying various diseases and biological phenomena, paving the way for the development of targeted therapies that promise widespread benefits.


In September 2023, Dr. Hou received the Maximizing Investigators’ Research Award (MIRA) for Early Stage Investigators (R35) from NIH/NIGMS to develop methods for inferring and analyzing gene regulatory networks using single-cell multiomics and spatial genomics data. Before that, as a postdoctoral fellow at Johns Hopkins Bloomberg School of Public Health mentored by Dr. Stephanie Hicks and Dr. Hongkai Ji, Dr. Hou received the NIH Pathway to Independence Award (K99/R00) (1K99HG011468-01) from NIH/NHGRI in March 2021 (mentors: Dr. Hongkai Ji, Dr. Stephanie Hicks, and Dr. Andrew Feinberg), to develop computational methods for inferring single-cell DNA methylation and its spatial landscape.