Advanced Seminars Abstracts

Seminar 1

Mobile Applications for Privacy-Preserving Digital Contact Tracing

Christos Laoudias, Steffen Meyer, Philippos Isaia, Thomas Windisch, Justus Benzler, Maximilian Lenkeit


Mobile applications for triggering Covid-19 exposure notifications without sacrificing the users’ privacy are a promising tool for complementing manual contact tracing that is a resource-demanding and labor-intensive task when the infections grow rapidly. This advanced seminar presents the fundamental concepts behind the realization of large-scale Mobile Contact Tracing Apps (MCTA). We provide an overview of this emerging field, while focusing on Bluetooth-based privacy-preserving solutions. We tackle the topic from multiple perspectives: background, state-of-the-art technologies, protocols, real-life implementations, performance indicators, security and privacy aspects, as well as future directions. The seminar presents the big picture, so that the target audience can further expand their knowledge by studying the material and following the references. Our presentation will be delivered through the lens of 2 country-wide MCTA, namely the Corona-Warn-App (CWA) and the CovTracer-Exposure Notification (CovTracer-EN) app deployed in Germany and Cyprus, respectively.

Seminar 2

Scalable Analytics on Large Sequence Collections

Karima Echihabi, Themis Palpanas


Data series are a prevalent data type that has attracted lots of interest in recent years. Specifically, there has been an explosive interest towards the analysis of large volumes of data series in many different domains, and in particular, in the Internet of Things (IoT). In this tutorial, we focus on applications that produce massive collections of data series, and we provide the necessary background on data series management and analytics. Moreover, we discuss the need for fast similarity search for supporting machine learning applications, and describe efficient similarity search techniques, indexes and query processing algorithms. Finally, we discuss the role that deep learning techniques can play in this context. We conclude with the challenges and open research problems in this domain.