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machine learning for transport simulation. A core innovation involves Bayesian metamodeling techniques to construct fast surrogate models of the simulation space, enabling efficient scenario analysis
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across the value chain. Using Bayesian Optimization / Modern Design of Experiment, we build the data-foundation to enable true hybrid development between humans and advanced learning algorithms such as
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at conferences and meetings. Participate in outreach activities including, but not limited to, social media updates, public events and campaigns, as well as dissemination to popular press. The exact research
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