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Bio

Konstantin Pieper joined ORNL in the Computational Science and Mathematics Division as a staff mathematician in June 2019 after obtaining his PhD at the Technical University of Munich (working with Boris Vexler) and a PostDoc at the Florida State University (working with Max Gunzburger). His research is focused on developing new optimization and discretization methods in the context of applications involving machine learning, optimal design of experiments, and climate modeling. Currently, he is applying infinite dimensional sparse optimization techniques to enhance the interpretability of neural networks and improve their training procedures.

Publications