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demographics remain lacking. This project proposes to bridge this gap by transferring state-of-the-art methods from humanoid robotics – reinforcement learning, whole-body model predictive control (MPC
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with data-driven models (hybrid modeling) for improved accuracy and generalization. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process
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produce research results in applied MPC Provide guidance and mentorship to graduate and undergraduate students working on related research projects Publish research findings in top-tier conferences
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privacy applications. The main application domains are: Lightweight/Ultra-lightweight cryptography Algebraic and Arithmetization-friendly cryptography for ZK and MPC applications Privacy enchancing