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.
22 maart 2020
Vacancy Assistant or Associate Professor in Security of Machine Learning
We are looking for a specialist on the interface of cybersecurity and machine learning who contributes to creating more robust methods for machine learning.
22 maart 2020
Vacancy Assistant or Associate Professor in Network Security
We are looking for a specialist in modern network security, who also can contribute to practical cybersecurity approaches such as capturing the flag and processing large scale network data sets to complement our existing expertise in research and education.
22 maart 2020
Dr. Kaitai Liang joins Cyber Security Delft
Dr. Kaitai Liang, currently assistant professor at the University of Surrey (UK), will join the cyber security group at EEMCS as of August 1, 2020.
01 maart 2020
Graph-Time Spectral Analysis for Atrial Fibrillation
Atrial fibrillation is a clinical arrhythmia with multifactorial mechanisms still unresolved. Time- frequency analysis of epicardial electrograms has been investigated to study atrial fibrillation. How- ever, deeper understanding of atrial fibrillation can be achieved if the spatial dimension can be in- corporated. Unfortunately, the physical models describing the spatial relations of atrial fibrillation signals are complex and non-linear; hence, the conventional signal processing techniques to study electrograms in the joint space, time, and frequency domain are less suitable. In this study, we wish to put forward a radically different approach to analyze atrial fibrillation with a higher-level model.
27 februari 2020
IEEE Open Journal on Signal Processing
Zeki would like to invite you all to consider sending your work for the papers around privacy enhancing technologies.