
Extracting meaningful information from EEG and neural signals with advanced signal processing.
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Continuous physiological monitoring with everyday wearable devices and smart algorithms.
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Scalable algorithms that run across networks of sensors, without a central node.
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Data-driven tools that help clinicians make better decisions at the point of care.
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Foundation methods for biomedical signals — from EEG to vitals to wearable streams.
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Patient-specific computational models for personalized medicine and simulation.
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Tailoring diagnostics and therapies to the individual using biomedical data and machine learning.
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Interpretable models that justify their predictions — essential for clinical adoption.
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Generative models that produce privacy-safe data for training and benchmarking.
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