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the following is desired: radio system modeling, electromagnetics, antennas, propagation, RF frontends, radar. Demonstrated expertise in channel modeling and characterization Hands-on experience with RF and/or
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/functional inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and
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processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental
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of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or experimental means. The PDA is expected to actively disseminate results through publications in
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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initial phase will employ machine learning models, computer vision algorithms, and real-time sensory integration to prototype tools such as SafeCross for safe street crossing and EasyPath for indoor
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multi-agent autonomous systems and related technologies. This will include development of distributed monitoring algorithms enabling agents in a multi-agent swarm to autonomously locate other agents in
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complex sociotechnical systems Strategic learning and equilibrium-seeking algorithms in transportation networks Game-theoretic approaches to cybersecurity and security games Integration of human behavior
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), Machine Learning on Quantum Computers, Security of Quantum Circuits, Design Automation and Tools for Quantum Circuits, Robust and Efficient Mapping of Quantum Algorithms on Quantum Machines, Quantum Noise