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candidates for next-generation electronic devices, energy storage systems, sensors, and catalysts. However, they also pose unique challenges from a machine learning perspective, calling for novel machine
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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