Cornelia Rauh

Papers

Total Citations

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About

Cornelia Rauh is a leading figure in food process engineering, whose work bridges artificial intelligence, robotics, and food formulation. Her research centers on the intelligent automation of food manufacturing, with a particular focus on optimizing complex food matrices and extrusion processes. Rauh’s major contributions lie in pioneering the use of active learning and robotics to solve multi-objective optimization problems in food production. In her highly cited 2022 work, she demonstrated how robotic systems combined with machine learning can efficiently navigate vast formulation spaces, drastically reducing the time and resources needed to develop new food products. Her 2025 study extends this paradigm to low-moisture food extrusion, introducing a closed-loop framework that integrates extrusion, on-line sample characterization, and multi-objective Bayesian optimization. This breakthrough enables real-time, automated adjustment of processing parameters to achieve a predefined set of quality objectives, visualized through Pareto front analysis. While her citation counts are still growing, reflecting the novelty of her approach, Rauh’s work is already recognized as transformative for the food industry, promising a future where product development is faster, more sustainable, and data-driven.