FWF - DENISE - Doctoral School for Dependable Electronic-Based Systems

Electronics-based systems (EBS) are becoming more and more prevalent in production, infrastructure and transport, but are only accepted if people trust these systems. Reliability is therefore becoming the cornerstone for the social acceptance of electronics-based systems. The researchers in the doctoral programme Dependable ElectroNIc-Based SystEms (DENISE) will explore concepts, methods and application-oriented tools to make EBS more reliable. The project deepens the very good relationship between FH Joanneum and Graz University of Technology through a joint doctoral programme. DENISE creates an integrated research framework across disciplinary boundaries and links reliability concepts of sensors with networked embedded devices. Existing strengths will be built upon and by pooling complementary expertise DENISE will lead to sustainable progress in the EBS sector.
Staff member
Konsortialführer/in bzw. Koordinator/in bei Kooperationen mit externen Organisationen
Christian Vogel
FH.-Prof. Dr. DI
Project Manager at the Organizational Unit
Annette Mütze
Univ.-Prof. Dr.-Ing.
Kay Uwe Römer
Univ.-Prof. Dipl.-Inform. Dr.sc.ETH
Participant / Staff Member
Carlo Alberto Boano
Assoc.Prof. Dott. Dott. mag. Dr.techn. MSc
Abd Alrahman Dawara
lj. M.Eng.
Florian Mayer
Dipl.-Ing. BSc
Mohamed Hassaan Mohamed Hydher
BEng MSc
Sayyidshahab Nabavi
Olga Saukh
bak. Assoc.Prof. Dr.rer.nat. MSc
Joachim Schauer
Assoc.Prof. Dr. DI
Markus Schuß
Dipl.-Ing. Dr.techn. BSc
Funding sources
  • Österreichischer Wissenschaftsfonds FWF, FWF
External Partners
  • FH JOANNEUM Gesellschaft mbH
Start: 30.04.2022

Publications

2024
Sayyidshahab Nabavi, Joachim Schauer, Carlo Alberto Boano and Kay Römer APOTSA Show publication in PURE
2023
Mohamed Hassaan Mohamed Hydher, Markus Schuß, Olga Saukh, Carlo Alberto Boano and Kay Uwe Römer Automatic Parameter Exploration for Low-Power Wireless Protocols Show publication in PURE
Francesco Corti, Balz Maag, Christopher Hinterer, Julian Rudolf, Joachim Schauer and Olga Saukh Poster: Resource-Efficient Deep Subnetworks for Dynamic Resource Constraints on IoT Devices Show publication in PURE
2022
Francesco Corti, Rahim Entezari, Davide Bacciu, Sarah Hooker and Olga Saukh Studying the impact of magnitude pruning on contrastive learning methods Show publication in PURE
Overview
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