41 Skylar E. Stolte Computer Vision News Computer Vision News adaptation, uncertainty quantification, and digital twins to enhance both accuracy and trustworthiness. Her models outperform traditional pipelines in terms of speed, segmentation fidelity, and robustness to population diversity. Importantly, they offer clinicians a practical pathway to move from populationlevel averages to individualized treatment planning. By simulating how current flows across each person’s brain, these models enable more targeted, effective, and precision neuromodulation. With a rare blend of technical rigor and translational vision, Skylar’s work lays the foundation for a new generation of patient-specific neurotechnology. We are excited to see what she does next! Sample segmentations from the T1-weighted MRIs of four participants, shown in the coronal view. Columns represent different participants; rows correspond to segmentation models. Each result displays the full set of tissue types segmented by the respective method. GRACE segments more tissue classes compared to other 3D methods. It also outperforms all state-of-the-art approaches on older adult data, including common brain tissue structures identified by other methods.
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