Ziqi Zhang

Machine learning Computational biology Single-cell sequencing data Algorithms for high-throughput multi-omics biological data Research description Professor Zhang’s research lies at the intersection of machine learning and computational biology, with a focus on developing methods for large-scale single-cell sequencing data. He studies representation learning across modalities and conditions, predictive modeling of cellular responses to perturbations, gene regulatory and cellular interaction network inference to uncover functional mechanisms, and the development of single-cell foundation models pretrained on large biological atlases. His long-term goal is to build interpretable computational models that capture biological heterogeneity and enable clinically relevant prediction at the patient level.

Ziqi Zhang is Assistant Professor at the University of Waterloo, affiliated with Computer Science. This summary considered 4 collected sources. Listed research or teaching areas include Machine learning Computational biology Single-cell sequencing data Algorithms for high-throughput multi-omics biological data Research description Professor Zhang’s research lies at the intersection of machine learning and computational biology, with a focus on developing methods for large-scale single-cell sequencing data. He studies representation learning across modalities and conditions, predictive modeling of cellular responses to perturbations, gene regulatory and cellular interaction network inference to uncover functional mechanisms, and the development of single-cell foundation models pretrained on large biological atlases. His long-term goal is to build interpretable computational models that capture biological heterogeneity and enable clinically relevant prediction at the patient level..