The Department of Computer Science and Statistics is hosting a presentation about Single-cell gene expression spatial and temporal modeling with deep learning. Ritambhara Singh, an Associate Professor of Computer Science and Data Science and a member of the Center for Computational Molecular Biology at Brown University, will present her team's efforts to build deep learning frameworks and leverage existing single-cell gene expression measurements to overcome technical constraints on the ability to collect all datasets at single-cell resolution. Singh will discuss scGraphHiC, which performs graph deconvolution to extract genome-wide single-cell spatial interactions from bulk contact maps using single-cell gene expression as a guiding signal, and scNODE, which predicts single-cell gene expression at missing time points to enable cell developmental analysis. Singh is an Associate Professor of Computer Science and Data Science and a member of the Center for Computational Molecular Biology at Brown University.