Lecture Series 2020

Lecture at Leipzig University in the master’s program Data Science

Coordinator: Prof. Dr. E. Rahm (Leipzig University) 

The aim of the lecture series was to give participants an overview of current requirements and solutions for methods, technologies and applications of Artificial Intelligence and Big Data. The focus was on the areas worked on at ScaDS.AI Dresden/Leipzig. Speakers included Principal Investigators actively involved in ScaDS.AI Dresden/Leipzig. The lecture was offered as part of the module Current Trends in Data Science (5 LP) of the new study program Data Science. Languages of lecture were German and English. Successful completion of the module required watching video lectures as well as successfully solving a practical task in teams of two. The results of the practical tasks were presented by the students in the last two video lectures. Furthermore, participation in the lecture series was open to other students, researchers and interested parties. 

Due to the Corona development, the lecture was held with video presentations. The lecture materials could be viewed via the online platform Moodle.

Schedule

Lecture	Lecturer	Content
1	Prof. Dr. Erhard Rahm	Introduction to ScaDS.AI and lecture series/module, ScaDS.AI topics of database group (data integration for knowledge graphs, privacy-preserving data analysis, analysis of dynamic graph data)
2	Prof. Dr. Stephanie Schiedermair	Datenschutz und Diskriminierungsverbote als Herausforderungen für KI
3	Dr. Sebastian Hellmann	Rapid Prototyping of Large Knowledge Graphs and their Applications such as AI
4	Prof. Dr. Martin Bogdan	Wie weit ist es bis zur Singularität?
5	Prof. Dr. Norbert Siegmund	Validity and Fairness in Machine Learning: A Software Engineering Perspective
6	Dr. Stefan Franke, Prof. Dr. T. Neumuth	Möglichkeiten und Grenzen der KI in medizinischer Forschung und klinischem Alltag
7	Dr. Ringo Baumann, Prof. Dr. Gerhard Brewka	Computational Models of Argumentation
8	Prof. Dr. Peter Stadler	Very Big Data in Computational Biology — Processing and Integration
9	Prof. Dr. Nihat Ay	Prof. Dr. Nihat Ay
10	J.Prof. Dr. Martin Potthast	Technologies for Information Retrieval and Summarization
11		Presentation of Results of Practical Exercises via Videoconference
12		Presentation of Results of Practical Exercises via Videoconference

Lecture Series 2017

Joint lecture at TU Dresden and Leipzig University

Coordinators: Prof. Dr. S. Gumhold (TU Dresden), Prof. Dr. E. Rahm (Leipzig University) 

The aim of the lecture series was to give participants an overview of current requirements and solutions for Big Data technologies and applications. The focus was on the areas worked on in the Big Data competence center ScaDS Dresden/Leipzig. Speakers were professors actively involved in ScaDS Dresden/Leipzig. 

The lecture took place in blocks of 2 lectures (each about 1 h) alternating at Leipzig University (lecture hall 8) and at TU Dresden (Willersbau A317). All lectures were streamed via video to the other location on the same day and could be followed in the specified auditorium.

The lecture series was aimed at students of the bachelor’s and master’s programs in computer science, PhD students and all interested parties. The accounting modalities for students were regulated site-specifically according to the framework conditions of the respective study programs.

Schedule

The first named location provides video streaming. Since the lecture is held in German, the seminar schedule is also in German.

Lecturer	Content
Block 1: 27. April, 15:00: Universität Leipzig, Hörsaal 8; TU Dresden, Willersbau A317
Prof. Rahm	Einführung in die Ringvorlesung und ScaDS Dresden/Leipzig
Prof. Rahm	Graph-based Data Integration and Analysis for Big Data
Prof. Scheuermann	Merkmalsbasierte visuelle Analyse großer wissenschaftlicher Daten
	Vorstellung/Vergabe der praktischen Aufgaben
Block 2: 11. Mai 2017, 15:00: TU Dresden, Willersbau A317; Universität Leipzig, Hörsaal 8
Prof. Sbalzarini	The PPML language for distributed scalable processing enables real-time segmentation of large image data
Prof. Lehner	Next-Generation Hardware for Data Management – more a Blessing than a Curse?
	Vorstellung/Vergabe der praktischen Arbeiten
Block 3: 18. Mai 2017, 15:00: Universität Leipzig, Hörsaal 8; TU Dresden, Willersbau A317
Prof. Stadler	Genome Annotation in the Age of Big Data
Prof. Heyer	Big Data in den Digital Humanities?
Block 4: 1. Juni 2017, 15:00: TU Dresden, Willersbau A317, Universität Leipzig, Hörsaal 8
Prof. Nagel	Big Data and HPC – Two worlds apart or common future?
Dr. Bussmann	Big Data in Photon Science: Why we do everything once
Block 5: 22. Juni 2017, 15:00: Universität Leipzig, Hörsaal 8; TU Dresden, Willersbau A317
Prof. Bogdan	Verbesserung der Sicherheit von Virtuellen Maschinen für Big Data Architekturen
Prof. Franczyk	Prozesse treffen Big Data – Verbindung zwischen Data Science und Prozess Science
Block 6: 29. Juni 2017, 15:00: TU Dresden, Willersbau A317; Universität Leipzig, Hörsaal 8
Prof. Gumhold	Scalable Visualization
Prof. Dachselt	Multimodal Exploration of Large Data Sets