Projects
In 2023, St. Pölten UAS’s 126 research projects generated revenue of EUR 5.6 million. Interdisciplinary projects have grown in importance in recent years as a means to identify suitable answers to modern-day issues and devise appropriate solutions.
GedMig- Multilingual Memory of Migration. Pupils interview Grandparents.
Citizen Science project to give more attention to (post)migrant groups and draw a more realistic picture of diversity in society.
JuSpAk
The perspective of users on offers of Lower Austrian youth vocational assis-tance in the tensionfield between activation policy and socio-pedagogical support.
ABC - Austrian Blockchain Center
K1 competence center with the goal of the scientifically based further development of the blockchain technology and its application in various economic sectors. These range from Industry 4.0/Internet ...
VRinMotion
Investigates how characteristics of stop-motion animation and motion-capturing can be conflated with virtual reality in order to enrich the current art discourse.
SSCCS - Secure Supply Chains for Critical Systems
Resilient and adaptable systems that are still operational after being attacked or affected by disruptive events.
Counter Speech - Young People Against Online Hate
Computer-assisted Strategies for Facilitating Citizen-generated Counter Speech in Social Media
TransSoDia – Transnational and Digital Learning and Teaching in Cooperative Social Diagnostics
Further Development of Tried and Tested Social Work Methods for Transnational Teaching at Multiple Universities.
SBA Research
K1 competence center for Information Security
TopDrone
Using drones to support the intermodal logistics chain in rail freight transport.
E+DIETing_LAB- Digital Lab for Education in Dietetics combining Experiential Learning and Community Service
New ways of educating and upskilling teachers, students and experts in the field of dietetics.
SoniVis
Working towards a unified framework for joint audio &visual analytics
IMREA - Intelligent Multimodal Real Estate Assessment
Multimodal information extraction and machine learning techniques for the extraction of real estate related attributes and parameters from heterogeneous input data