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Field
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include: Developing and analyzing representative dynamic simulation scenarios for electrical power systems Extending kernel-based Gaussian Process methods for the estimation of electrical and control
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an adversary. We would like to address the safety concerns by researching a metrology for establishing digital references [2], safety zones (boundaries), validation methods for AI risk management, and
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, MPC), state estimation, system identification and design synthesis problems. A key characteristic of dynamic optimization problems (DOPs) is that the decision variables can be functions or trajectories
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types. Develop methods to translate structural damage severity into functional-impact and risk classifications for critical vessel subsystems. Develop data-driven or physics-informed surrogate models
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field robotics and tests its methods on robots in real environments. We are now looking for a postdoctoral researcher to develop sensing and autonomy for drones that inspect infrastructure and terrain in
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that understand both what the user intends to do and what is happening in the environment. The PhD will focus on the computational and sensing methods required to make such systems robust, generalizable
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Protected Volume estimation, navigation, decision-making, and control modules within a simulation-based validation framework. Develop methods to estimate the maximum safe operational capacity for drone
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: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal prediction). O3: Joint OOD detection + AL: Combine
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: Robust uncertainty estimation: Improve calibration and uncertainty reliability under drift (e.g., ensembles, Bayesian approximations, conformal prediction). O3: Joint OOD detection + AL: Combine
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volume estimation, navigation, decision-making, and control modules within a simulation-based validation framework. Develop methods to estimate the safe operational capacity for drone operations under