How does smart toys’ surveillance affect our children? Does the digital euro turn us into transparent citizens? Can our privacy still be saved? Digital data traces concern us all. The public lecture series “Privacy in the Digital World” at the University of Salzburg presents current research on privacy and data protection in the digital realm.

What do professors of philosophy, computer science, constitutional and administrative law, and the data protection officer of the University of Salzburg have in common? They are the organizers of this public lecture series, which addresses the topic of privacy from an interdisciplinary and cross-faculty perspective. The question of individual privacy in our increasingly digital everyday lives—whether in studies, work, or private life—affects us all. There are two extreme viewpoints: some see privacy as being threatened by new technologies, while others view bureaucratic barriers as obstacles to innovation.

Open house at the Departments of Computer Science and Artificial Intelligence and Human Interfaces (AIHI) at the University of Salzburg: projects, presentations, and up-to-date information about studying and research.

We invite students to explore the Artificial Intelligence and Computer Science degree programs and offer everyone interested the opportunity to get a behind-the-scenes look at the departments. We will showcase projects from our research groups and aim to spark interest in computer science through interactive workshops and presentations.

Four research papers from the “Big Data Algorithms” research group have been accepted for presentation at the A*-ranked ACM-SIAM Symposium on Discrete Algorithms (SODA). SODA is the top conference in the field of algorithms and one of the most prestigious conferences in theoretical computer science. In 2025, the conference will take place in mid-January in New Orleans.

The “Big Data Algorithms” research group has been based at the University of Salzburg since 2022 and is led by Prof. Sebastian Forster. All four publications were developed as part of the DynASoAr project, funded through an ERC Starting Grant secured by Forster. The goal of the project is to study dynamic algorithms that can efficiently adapt to changes in input data.