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of hybrid intelligence teams; developing a run-time computational framework to automatically assess these metrics; automatically measuring and analyzing interactions between hybrid team members; creating
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network (based on U-net, e.g. similar to MitoNet that we used before on FAST-EM data) to automatically segment organelles from FAST-EM imaging data, with a focus on WPBs, endolysosomal compartments and
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real-to-sim-to-real pipelines that automatically construct simulation environments from video recordings or images of real-world robotic tasks, enabling scalable and low-cost training data generation
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