Research projects - Ubiquitous Computing and Interaction - Department of Computer Science

ArtiPlex

The ArtiPlex project sets out to revolutionize the current artifact detection paradigm by integrating the results of multiple detection methods running in parallel. The key innovation lies in proposing “Multiplex Analytics” - a concept designed to progressively visualize the stream of multiple, automated detection results.

CCTD - Center for Computational Thinking and Design

Center for Computational Thinking and Design (CCTD) is a new interdisciplinary center at Aarhus University. The center has the Department of Computer Science, the School of Communication and Culture, and the Department of Management as the primary actors.

CEED project

CEED is a 4-year research project exploring and building new practices of computational empowerment for emerging technologies in Danish secondary education.

CoThinker

The CoTinker project addresses the development and design of an open source infrastructure that enables the development of new learning tools within computational thinking (CT) to support collaboration and flexibility in learning environments.

DABAI

The vision of the “DAnish center for Big data Analytics driven Innovation” (DABAI) is to place world-class computer science Big Data analysis research and innovation at the core of an effort to seize opportunities in domains of importance to Danish businesses and society.

HealthD360

The aim of “360 Degree Health Data Integration” (HealthD360) is to develop an integrated data platform that combines today’s fragmented landscape of health-related data sources – in particular from various wearable sensors – for coherent, personalized treatment.

MADE digital

The research in MADE Digital work package 6, Digital Assistance Tools, focuses on how augmented reality and virtual reality can be used in manufacturing context.

MCTIG - Computational Thinking in Humanities, Arts and Social Sciences

Computational thinking in secondary education and professional development of high school teachers in humanities, arts and social sciences.

VADE

The project “Visual Analytics of Data Errors” looks for better ways to identify and analyze data quality issues through the use of Mixed-Initiative Analytics.

Current projects