Our graduate Barbara Pedretscher studied Technical Mathematics. She completed her compulsory internship at KAI Kompetenzzentrum Automobil- und Industrieelektronik GmbH and was subsequently invited to write her diploma thesis and doctoral dissertation there as well. Today she works in the field of R&D Reliability and Data Science. We chatted with her about the many possibilities afforded by a university education and about spending memorable years at university. Read more
Established within the university’s Digital Age Research Center (D!ARC) the Cybersecurity research group goes into it’s second year of activities. The group’s research areas are based within cryptography, statistical machine learning, embedded security, artificial intelligence and deep learning as well as crypto engineering.
The group’s main expertise is in the area of deployment aspects of cryptography. Such aspects are related to information leakage (via side channels), and the detection and prevention of such channels; practical cipher constructions for specific application areas; secure implementation techniques and tools; and the application of machine learning and deep learning in the context of cybersecurity.
The Cybersecurity research group is currently running an ERC funded Consolidator Grant project, titled SEAL („Sound and Early Assessment of Leakage for Embedded Software“). It tackles the challenge to developed tools that are sophisticated enough to predict a range of side channel leakage behaviours for modern processors.
In the last months the team has grown to the number of ten. Currently the group consists of one professor, one lecturer, three postdocs, three PhD students, one technician and one administrator. The group represents five different countries, making work and communication a truly international and cultural experience.
You will find more information here:
If you are interested to explore collaborations in any shape or form, let’s talk!
Please email to Elisabeth [dot] Oswald [at] aau [dot] at
That life opens up paths you never expected is something Johannes Hofmeister, a doctoral student in statistics, experienced only recently. He told us why he decided not to become a teacher (for now), but has become an avid mathematical researcher instead.
Our graduate Michael Tarmastin started working for Infineon Technologies Austria AG (Infineon Austria) as an industrial trainee while he was still studying for his Bachelor’s degree in Information Management. He was offered the opportunity to write his diploma thesis there and to take up a full-time position. As a Senior Operations Manager at Infineon in Villach he is now responsible for 120 employees and he talks to us about regarding the Welcome Days as the launch pad for an unforgettable time at university and the responsibility he now bears for his department. Read more
Our graduate Margareta Ciglič discovered her passion for Computer Science while studying Applied Business Administration and decided to study both in parallel. We chatted with her about how all this came about, what her subsequent path at the university and at Kelag Energie has been like, and what is drawing her back to the lecture halls of the University of Klagenfurt in the upcoming summer semester. Read more
Kathrin Spendier from the Institute of Statistics at the University of Klagenfurt and member of the Austrian Science Fund FWF doc.funds doctoral school Modeling—Analysis—Optimization is Carinthian of the Day!
Die AAU Klagenfurt / TeWi – Abteilung Artificial Intelligence und Cybersecurity – sucht ab März 2021 eine Studienassistentin (7 h/Woche).
Umstellung der PPTX-Folien von Systemsicherheit auf LaTeX und Erweiterung und Pflege der SPU-Fragen für “Algorithmen und Datenstrukturen”, “Einführung in die theoretische Informatik” und “Systemsicherheit”
– Organisationstalent und die Bereitschaft zur raschen Einarbeitung.
Formlose Bewerbungen an Peter Schartner erbeten.
The volume of socio-economic data has risen significantly in recent years. At the same time, its complexity is steadily increasing. A closer look at the data that is compiled for decision-makers reveals that we are far from making full use of the ever-growing mountain of data. A team of researchers drawn from the fields of statistics, machine learning, economics, social sciences and computer science is seeking to develop new methods that will allow the extrapolation of improved conclusions from the data. The project is funded by the Austrian Science Fund FWF.
Verena Schwarz came to Klagenfurt to join the FWF doc.funds doctoral programme on “Modeling – Analysis – Optimization of discrete, continuous, and stochastic systems”. We spoke with her about the origins of her passion for mathematics.
When it comes to computer science, we can develop large, complex applications as a single monolithic system, or we can split them into small, scalable components that work together using standard protocols. In the Internet cloud, these small components are often implemented as microservices. A new research project, funded by the Austrian Research Promotion Agency, sets out to understand more precisely how changes in a single microservice affect other microservices and the application as a whole. Read more