One pervasive trend is to quantify more and more aspects of the world and our lives through data. Datafication is radically influencing the way people, companies, societies, and governments exist and operate. This creates new opportunities as well as new hazards. The INSY department aims to enable man and machine to deal with the increasing volume and complexity of data, in close cooperation with their environment.
Together with the software technology department, INSY is responsible for the Computer Science bachelor programme and the two master tracks, Software Technology (ST) and Data Science & Technology (DST). The department also contributes to the Computer Science specializations Cybersecurity, Bioinformatics, and EIT Innovation of the master in Digital Media Technology.
The department integrates fundamental research, engineering and design in the interlocking fields of data processing, interpretation, visualization and interaction using model- and knowledge-based methods and algorithms. The research is inspired by challenges from the domains of consumer electronics and entertainment, cultural heritage, social media, medical and health sciences, security and privacy, and safety and incident management. The department underpins the EEMCS thematic research lines Data Science, Safety & Security, and Health & Wellbeing.
12 mei 2019
Odette Scharenborg Associate Editor
Odette Scharenborg has been appointed as an Associate Editor of the IEEE journal Signal Processing Letters. The IEEE journal Signal Processing Letters is one of the flagship journals of the IEEE Signal Processing Society
12 mei 2019
The Multimedia Computing Group cordially invites you to a Music Information Retrieval morning seminar, Wednesday, May 15, Social Data Lab.
The Artificial Intelligence Lab at the Otto von Guericke University Magdeburg is dedicated to improving the cognitive abilities of machines and reducing the friction in human-machine interaction. We investigate novel signal processing and deep learning algorithms for the analysis of sensory data and investigate human-centric approaches to interacting with machines such as speech, EEG or eye tracking. This opens up richer communication channels to remedy the interface bottleneck between human and machine and introduces feedback mechanisms that make communication more robust.
05 mei 2019
’10 seconds of fame’ for Odette Scharenborg
’10 seconds of fame’ for Odette Scharenborg in a RAI-item on Sicilian TV about the International Workshop on Spoken Dialogue Systems Technology in Siracusa, Italy. In the fragment, Odette explains how machines can learn to recognise words from neural signals.
30 april 2019
Article in Nature's Scientific Reports: Information Diffusion Backbones in Temporal Networks by X. Zhan, A. Hanjalic and H.Wang
Progress has been made in understanding how temporal (time-evolving) network features affect the percentage of nodes reached by an information diffusion process, i.e. the prevalence of information, epidemic and opinion.
14 april 2019
Odette Scharenborg published in Speech Communication
The paper provides a systematic review of the literature on non-native spoken-word recognition in the presence of background noise, and posits an updated theory on the effect of background noise on native and non-native spoken-word recognition.