Faculty of Computer Science

Research

With more than 300 scientific and administrative staff members, our Faculty participates in many national and international cooperation projects, working with economic and scientific partners.

In addition to addressing current issues, these collaborations facilitate research-oriented teaching and enable advanced students to become involved in an attractive, international research environment.

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Our key research areas

In accordance with the development plan of the University of Vienna, our Faculty’s academic focus is centred on the four key research areas Algorithms, Data Science, Systems, and Human-Centered Computing.

Research around the globe

The researchers in our Faculty are globally connected and collaborate regularly with colleagues from all over the world. A visual representation of our collaborations at international and regional level is available in the u:cris research database.

View collaboration map

Academic work

Firmly established as key components of academic work, the projects and publications of our researchers promote an exchange of knowledge, document research findings and enhance our Faculty’s international profile.

  • Projects

Foundations and Applications of Resource-Restricted Cryptography (FARCry)

Azari, Karen (Project Lead), Pietrzak, Krzysztof (Co-Lead), Schröder, Dominique (Co-Lead)
01/10/2026 30/09/2030
Active

Design-Level Vulnerabilities Identification and Fixing

Zdun, Uwe (Project Lead), Suman, Orwa (Scientific Project Staff), Ennsberger, Sylvia (Admin)
01/09/2026 31/08/2029
Active

Symbolic Timing Analysis of Asynchronous Circuits

Ferdowsi, Arman (Project Lead), Aral, Atakan (Mentor), Ennsberger, Sylvia (Admin)
01/08/2026 31/07/2029
Active

  • Publications

Distributed neuromorphic computing with temporal co-optimization of spiking dynamics. / Ferdowsi, Arman; Aral, Atakan.
In: Future Generation Computer Systems, Vol. 188, 108805, 03.2027.

Publications: Contribution to journal › Article › Peer Reviewed

doi.org/10.1016/j.future.2026.108805
www.scopus.com/pages/publications/105051699760

CAR-MNAR: A Unified Factorial Framework for Robust Causal Discovery Under Self-masking MNAR. / Alinejad, Matin; Hlavackova-Schindler, Katerina.
Machine Learning and Knowledge Discovery in Databases. Research Track. ed. / Michelangelo Ceci; Dragi Kocev; Anna Monreale; Celine Vens; Peter Flach; Giuseppe Manco; Myra Spiliopoulou; Elio Masciari. Cham: Springer Nature Switzerland AG, 2027. p. 603-622.

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

www.researchgate.net/publication/413589992_CAR-MNAR_A_Unified_Factorial_Framework_for_Robust_Causal_Discovery_Under_Self-masking_MNAR#fullTextFileContent

Timed Lossy Trapdoor Functions and Their Applications. / Abusalah, Hamza; Azari, Karen; Consbruch, Maximilian von.
Asiacrypt 2026. 2026.

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed

http://eprints.cs.univie.ac.at/8793/

Local drivers of anthropogenic forest fire ignition vulnerability in Austria. / Wimmer, Elisabeth (Corresponding author); Mallinger, Kevin (Corresponding author); Corpaci, Luiza et al.
In: Fire Ecology, Vol. 22, No. 1, 59, 12.2026.

Publications: Contribution to journal › Article › Peer Reviewed

doi.org/10.1186/s42408-026-00496-2
www.scopus.com/pages/publications/105040394111

ObfuscationGT: A Comprehensive Evaluation of Disassembler Accuracy and Coverage on Obfuscated Code. / König, Caroline; Felbauer, Patrick; Pucher, Michael et al.
International Symposium on Research in Attacks, Intrusions and Defenses 2026. 2026.

Publications: Contribution to book › Contribution to proceedings › Peer Reviewed