Wiebke Köpp is a Computational Research Scientist at Berkeley Lab, focusing on the development and deployment of scientific workflows for experimental design, data management, analysis, and visualization. Prior experience includes serving as a PhD student at KTH Royal Institute of Technology, where Wiebke engaged in research on the visualization and analysis of dynamic hierarchies from large-scale flow simulations and taught graduate courses in visualization, computer graphics, and machine learning. Additional roles include Research and Teaching Assistant and Teaching Assistant at Technische Universität München, contributing to research on adaptive transfer functions and assisting in various undergraduate courses. Wiebke's educational background includes a PhD in Computer Science with a focus on High Performance Computing and Visualization from KTH, a Master of Science in Engineering from KTH, and a Master's and Bachelor's in Informatics from Technische Universität München.
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