TUna was launched as one of the eleven major fuTUre fit projects and has a clear goal: to help students better navigate everyday university life. This user-centered tool will not only be technically innovative, but will also be closely coordinated with student councils, Student Support, and the various faculties. The result will be a needs-based, practical and data-protection-compliant digital assistant, developed with the involvement of numerous members and departments of TU Wien. In this way, TU Wien not only uses digital technologies as a subject of research but also drives forward digital transformation within its own institution, fully in line with TU Wien’s strategic objective No. 4.
Project Profile
Project leaders: Julia Neidhardt and Thomas E. Kolb
Who is involved in the project?
TUna is carried out by the Data Science Research Group in collaboration with the Data Science Team at dataLAB and an interdisciplinary team from the fields of research, software development, and university services. The project is carried out in collaboration with Student Support, the Admissions Office, the Dean’s Office of the Faculty of Computer Science, the Student Union at TU Wien (HTU), and the Doctoral Student Council (FSDr). These partners contribute domain expertise, operational perspectives, and the student viewpoint to ensure that TUna fits real needs and can be sustainably integrated into TU Wien’s service landscape.
Who is this project for?
The focus is on students and answering their study-related questions. TUna supports students in navigating study and university life by providing quick, reliable answers and clear guidance across common questions and processes. It is designed for everyday use, especially when information is distributed across different portals and websites. Service and counseling centers also benefit from this, as TUna aims to reduce recurring standard inquiries and improve the process of directing users to the right information and contacts.
What makes the project special?
TUna combines a user-centered approach with trustworthy AI practices. It is designed to cite reliable sources, ensure user-friendliness and fairness, and continuously improve through structured feedback loops. The system is operated on-premises and adheres to the principles of “Privacy by Design” as well as careful handling of logging and access. TUna also has a modular structure, allowing additional data sources and features to be integrated over time.
What changes will it bring to TU Wien?
TUna helps students find reliable information and complete routine tasks with fewer obstacles. It will assist the service units by reducing the number of frequently asked questions and improving the consistency of responses. In the long term, the project will enhance the quality of TU Wien’s digital services and provide a reusable model for responsible AI-powered support services within the university.
What is the current status, and what are the next steps?
The project started on 1 January 2026 and runs for one year. It is structured in phased work packages that move from requirements gathering to data integration, prototype development, and evaluation.
Over the past few months, interviews have been conducted with various advisory bodies at TU Wien and HTU, and an initial prototyping phase has already been completed. The next steps include integrating multiple production data sources, building a functional prototype with tool invocation and user storage, and conducting usability and fairness evaluations with iterative improvements.
Contact
Assistant Prof. Dr.in Julia Neidhardt & Univ. Ass. Dipl.-Ing. Thomas E. Kolb
TU Wien, Faculty of Informatics
Institute of Information Systems Engineering
Research Unit of Data Science
Dipl.-Ing. Daniel Niederlechner
TU Wien, Campus IT
Service Unit of High Performance Computing (dataLAB)
Contact via: tuna@list.tuwien.ac.at