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computational methods for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and
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-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination, safety and security issues. Besides robustness, systems should also be optimized for high performance and energy
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of computing and healthcare. Methodologies of interest include: multi-modal learning, foundation models, including large language models, agentic AI, multi-agent AI systems, transfer learning, self-supervised
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learning, foundation models, including large language models, agentic AI, multi-agent AI systems, transfer learning, self-supervised learning, and federated learning. The Postdoctoral Researcher will be
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area of research and development (R&D) of next-generation Edge-AI and Embodied-AI Systems with tiny-LLMs, tiny-VLMs, tiny-VLAs; Agentic-AI systems; and Robust Generative AI targeting hallucination