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hierarchical, contextual knowledge for complex multi-modal scene understanding Neuro-symbolic architectures for representation, learning, reasoning and inference Biologically-inspired metacognitive AI paradigms
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grammar & machine learning for inverse-designing polymers with targeted thermo-mechanical properties by tuning the polymer chemistry & architecture, catering to Artic & Space applications. The framework
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between various system and network architectural layers and relationships between respective protocol capabilities and characteristics, as well as networking analysis and/or decision analytic tools and
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involves developing numerical modeling techniques to achieve highly optimized, multidisciplinary physical modeling on scalable computer architectures. ARL Advisor: Yong-Le Pan ARL Advisor Email