Sabrina Herbst

Sabrina Herbst is a PreDoc Researcher at the Department of Computational Sustainability within the Faculty of Informatics at Technische Universität Wien. She works on Quantum Computing, focusing on Machine Learning integration and High-Performance Computing (HPC) augmentation for quantum algorithms.

• Education: Dipl.-Ing. (2023) in Informatics from TU Wien, with a thesis on quantum machine learning.

Her research explores scalable Quantum Machine Learning (QML) algorithms, emphasizing theoretical foundations and robust numerical implementations. Key areas include Quantum Neural Networks (QNNs), hyperparameter optimization, and the intersection of quantum computing with HPC and edge computing. Recent work investigates channel distinguishability in QNNs and hybrid quantum-classical systems for IoT data processing.

Projects she contributes to include HPQC (High Performance integrated Quantum Computing), Themis FWF (Trustworthy and Sustainable Code Offloading), and TRITON FWF (Transprecise Edge Computing). Awards include the Andreas Dieberger–Peter Skalicky Scholarship (2025), Siemens Award for Excellence (2023), and a conference scholarship from TU Wien (2024).

• Scientific Awards
  • Andreas Dieberger–Peter Skalicky Scholarship (2025)
  • Siemens Awards for Excellence (2023)
  • Conference Scholarship for female PhD students (2024)