Abstract:

In this talk, we discuss techniques for measuring the structural distance/similarity between networks. We start by outlining very basic concepts to do so and elaborate on some historical developments. Afterwards, we outline a novel technique for comparative graph analysis using topological indices and draw some conclusions.

Bio:

Prof. Dr. habil Matthias Dehmer studied Mathematics and Computer Science at the University of Siegen. Then his research areas became discrete mathematics, information theory, data analysis, data science, big data, and machine learning. In particular, he contributed extensively to complex network analysis and information theory. Finally he became one of the pioneers to establish an Information Theory of Networks.

His research is primarily concerned with the development of quantitative techniques to analyze structural properties of graphs. Also, he has been working on examining relationships between those techniques, for instance proving interrelations between quantitative network measures. The development and the application of those methods together with his experience, underpinned by a career spent both in industry as well as academia, has led to numerous contributions in the above mentioned areas.

He got a PhD in Computer Science from the Darmstadt University in Technology where his thesis ’Structural Analysis of Web-based Documents’ dealt with the problem of measuring the structural similarity of graphs. From 2005 to 2008, he held several research positions at the University of Rostock (Germany), Vienna Bio Center (Austria), Vienna Technical University (Austria) and University of Coimbra (Portugal). In October 2008, he got his habilitation in Applied Discrete Mathematics from the Vienna University of Technology. 

Afterwards, he started in April 2009 as Professor at the UMIT (Austria). In 2010, he got the Head of the Institute of Bioinformatics and Translational Research at UMIT. In particular, Prof. Dehmer has extensively been using methods from discrete mathematics (e.g., entropy, statistical estimation, optimization) to explore the structure of complex networks. In particular, he investigated the topological entropy of graphs extensively and used these concepts in other scientific fields. Currently he hold professorships at the UMIT and the University of Applied Sciences Upper Austria, Campus Steyr. In addition, he is guest professor at Nankai University at College of Computer and Control Engineering Nankai University.

Matthias Dehmer has more than 255 peer-reviewed publications in Applied Discrete Mathematics, Computer Science, Bioinformatics and related disciplines. Also, he recently established the novel book series „Wiley Series in Quantitative and Network Biology“ (Wiley- VCH) and „Network and Decision Sciences (CRC)“. Matthias Dehmer‘s  h-index equals 34 and his i10-index equals 106.