Yue Li
I completed my PhD degree in Computer Science and Computational Biology at University of Toronto in 2014. Prior to joining McGill, I was a postdoctoral associate at Computer Science and Artificial Intelligence Laboratory (CSAIL) at MIT (2015-2018).
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My research is focused on developing interpretable probabilistic learning models and deep learning models to model genetic, epigenetic, electronic health record, and single-cell genomic data. By systematically integrating multimodal and longitudinal data, I aim to have impactful applications in computational medicine including building intelligent clinical recommender systems, forecasting patient health trajectories, personalized polygenic risk predictions, characterizing multi-trait functional genetic mutations, and dissecting cell-type-specific regulatory elements that are underpin complex traits and diseases in human. My research program covers three main research areas involving applied machine learning in (1) healthcare and public health, (2) computational genomics, and (3) population genetics.
Bayesian inference, statistical genetics, topic models, electronic health records, deep generative models, multimodal data integration