Benita Nortmann

Vaughn College of Aeronautics and Technology, Imperial College London

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About

Benita Nortmann is a rising researcher at the forefront of data-driven control theory and dynamic game theory. Her work primarily focuses on developing algorithms that bypass the need for exact mathematical models, instead leveraging raw data to solve complex control and strategic interaction problems. Her most impactful contribution, published in 2024, introduces four novel iterative algorithms for computing Nash equilibrium strategies in discrete-time linear quadratic games—a notoriously difficult problem in multi-agent systems. This work has already garnered 16 citations, signaling its immediate relevance to the field. Nortmann’s research is distinguished by its practical orientation: she has demonstrated how data-driven methods can be applied to challenging real-world systems, such as the locomotion control of planar snake robots, where she proposed a robust, time-varying state feedback controller. Furthermore, she has advanced the theoretical underpinnings of optimal control by showing how quadratic objective functions can be represented directly from non-optimal data trajectories. Through her innovative fusion of game theory and data-driven control, Benita Nortmann is establishing herself as a key contributor to the next generation of autonomous and multi-agent systems.