Summary
Boyuan Liu is a Data Engineer and Technical Product Owner with a decade of interdisciplinary experience bridging biostatistics, biochemistry, and computational biology. Currently at Roche, he translates complex biological problems into scalable data products and previously developed a novel scRNA-seq clustering algorithm (scGMM-VGAE) combining variational graph autoencoders with Gaussian mixture models. His work blends hands-on deep learning (PyTorch), statistical rigor, and wet-lab insight from graduate research on GPCR structural dynamics, enabling pragmatic solutions that respect experimental nuance. Trained at the University of Toronto with top grades in Biostatistics and Biochemistry, he is comfortable moving between production data engineering and cutting-edge computational biology research. An uncommon strength is his ability to integrate domain-specific graphs and biologically informed priors into ML models, improving interpretability and downstream utility.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Biostatistics with Emphasis in Artificial Intelligence (AI) and Data Science, cGPA: A+, Master of Science - MS, Biostatistics with Emphasis in Artificial Intelligence (AI) and Data Science, cGPA: A+ at University of Toronto