QuantERA Call 2025 Partner Search Tool

General Information

• Type: Partner looking for project
• Organisation: University of Stavanger
• Country: Norway (NO)

Research area

• Call topics:
  • Applied Quantum Science
• Keywords:

  Trustworthy AI Quantum Machine Learning Cybersecurity Uncertainty Quantification Robust Learning

• Brief description of your expertise / expertise you are looking for:

  I am an Associate Professor of Cyber Security at the University of Stavanger, Norway, specializing in Trustworthy & Secure AI, uncertainty-aware deep learning, and robust machine learning for next-generation communication systems (5G/6G). My recent work includes developing uncertainty-aware quantum machine learning (QML) methods, secure and privacy-preserving learning architectures, and adversarial robustness frameworks for classical and quantum models. I contribute to research on: - Trustworthy & robust QML pipelines - Lipschitz-bounded and convex-geometry–based uncertainty quantification - Secure and privacy-preserving federated learning (FL) - Robust AI for wireless communication - LLM trust layers and self-diagnosis I am interested in joining or forming a consortium working on applied quantum computing, secure QML, hybrid classical–quantum AI architectures, and quantum-enhanced data analysis.

• Brief description of your project / the project you would like to join:

  I am interested in contributing to a project focusing on Trustworthy Quantum Machine Learning and its applications in real-world data analysis, communication networks, or secure decision-making. My proposed contribution includes developing: - Uncertainty-aware QML models using probabilistic, geometric, or convex-hull–based methods - Robustness and security evaluations for QML under noise, adversarial perturbations, and real-device imperfections - Hybrid quantum-classical pipelines for classification, regression, and generative modeling - Quantum-safe learning architectures, including privacy-preserving QML and secure QML workflows - Tooling and benchmarking frameworks for trustworthy QML I am open to joining existing consortia or helping shape a new consortium focused on applied and secure QML, quantum AI for communications, trust layers for quantum-enhanced models, or cross-domain quantum intelligence applications.

Ferhat Ozgur Catak

• Organisation: University of Stavanger
• Position: Associate Professor
• E-mail: f.ozgur.catak@uis.no
• Web: scholar.google.com/citations?hl=en&user=qPzUoDYAAAAJ&view_op=list_works&sortby=pubdate