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We are a multidisciplinary laboratory developing novel computational methods and tools for learning-based decision making and control of complex and partially unknown dynamical systems that are changing over time with applications in biomedical control systems, multi-agent systems, flight robotics, flight control and aerospace control. We are working toward autonomy by placing ourselves at the intersection of model-based control and machine learning. By taking aspects from both fields, we are able to adapt the control loop to real-life scenarios and changing environments.

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