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Microfluidic High-Throughput Methods for the Induction and Characterization of Repeatable, Titratable Traumatic Neural Injury in the Nematode Caenorhabditis elegans
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Applications of Deep Learning in Brain Injury Biomechanics and Spine Image Registration
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Applications of Machine Learning in Real-time Brain Tissue Strain Estimation
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Machine Learning Pipelines for Deconvolution of Cellular and Subcellular Heterogeneity from Cell Imaging
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Development of automated analysis methods for identifying behavioral and neural plasticity in sleep and learning in C. elegans
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RVD2: An ultra-sensitive variant detection model for low-depth heterogeneous next-generation sequencing data
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Automated whole-organism functional screening technologies and neurological disease models in C. elegans
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Statistical Methods for Characterizing Genomic Heterogeneity in Mixed Samples
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