About
Dr. Henning Bahl is affiliated with the Chair of Theoretical Physics II at Julius-Maximilians-Universität Würzburg. His research focuses on applying machine learning techniques to particle physics, particularly developing accurate surrogate models with calibrated uncertainties for LHC physics. He presented a seminar titled 'Accurate Surrogate Amplitudes with Calibrated Uncertainties' on 24 July 2025.
Key research interests include neural network architectures for precision physics, uncertainty quantification via Bayesian networks, and the integration of machine learning into high-energy physics workflows. His work emphasizes systematic testing of activation functions and heteroscedastic loss models for reliable surrogate amplitudes.
No scientific awards, grants, or advised students are explicitly mentioned in the provided texts. Contact details include the department address in Würzburg and phone +49 931 31-85877.
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