Yue Li

Yue Li is a researcher at McGill University's Department of Computer Science. Their work focuses on applied machine learning, bioinformatics, and computational biology, with an emphasis on AI methods for computational biology, particularly in population genetics, single-cell multi-omics, and electronic health records. Li's research includes developing machine learning techniques for translational impact in healthcare, such as multimodal EHR integration, time-series health forecasting, and Bayesian polygenic risk score inference. They are also involved in single-cell foundation models and genome foundation models for scATAC-seq analysis. Li's research has been published in journals such as Nature Communications, npj Digital Medicine, and the American Journal of Human Genetics.

Yue Li is a researcher at McGill University specializing in machine learning and computational biology. Their work focuses on integrating machine learning techniques with biological data to uncover insights into genetic mechanisms and cellular processes. Li's research includes analyzing large-scale genomic datasets to understand the genetic basis of complex diseases, such as tobacco and alcohol use, and exploring the role of RNA modifications in developmental regulation. They have also contributed to the development of computational tools for analyzing single-cell transcriptomic data and electronic health records. Their research bridges computational methods with biological systems to advance understanding of gene regulation and disease mechanisms.