FWF - DENISE - Doktorandenschule für zuverlässige elektronikgestützte Systeme

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.
Mitarbeiter*innen
Konsortialführer/in bzw. Koordinator/in bei Kooperationen mit externen Organisationen
Christian Vogel
FH.-Prof. Dr. DI
Projektleiter/in an der OE
Annette Mütze
Univ.-Prof. Dr.-Ing.
Kay Uwe Römer
Univ.-Prof. Dipl.-Inform. Dr.sc.ETH
Teilnehmer*innen / Mitarbeiter*innen
Carlo Alberto Boano
Assoc.Prof. Dott. Dott. mag. Dr.techn. MSc
Francesco Corti
Dott. Mag.
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
Fördergeber*innen
  • Österreichischer Wissenschaftsfonds FWF, FWF
Externe Partner
  • FH JOANNEUM Gesellschaft mbH
Beginn: 30.04.2022

Publikationen

2023
Mohamed Hassaan Mohamed Hydher, Markus Schuß, Olga Saukh, Carlo Alberto Boano and Kay Uwe Römer Automatic Parameter Exploration for Low-Power Wireless Protocols Publikation in PURE anzeigen
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 Publikation in PURE anzeigen
2022
Francesco Corti, Rahim Entezari, Davide Bacciu, Sarah Hooker and Olga Saukh Studying the impact of magnitude pruning on contrastive learning methods Publikation in PURE anzeigen