You can learn more about ongoing specific projects below.
FeaturedExplainability + Genomics
Dimensionality Reduction Algorithms with a focus on explainability for single cell transcriptomics experiments.
MorePhysics + ML
Physics informed machine learning tools for understanding self-organizing systems. Multi-agent simulations, graph neural networks and symbolic regression models for in silico active matter, developmental patterns and ecology.In vitro vs in vivo systems
Transfer learning and multi-modal learning for organoid to scRNA-seq integration and comparison. What gene regulatory signatures encountered in vivo are recapitulated in organoid cultures?Mechanics + Transcriptomics
Bayesian machine learning methods for inferring mechanical properties and morphological features of cellular aggregates with the goal of quantifying their interaction with transcriptomics.Infer + Perturb
Experimental design and multi arm bandits for optimal perturbations in transcriptomic studies.