Andreas  Holzinger Author of Evaluating Organization Development
FEATURED AUTHOR

Andreas Holzinger

Prof
Holzinger Group

Andreas is Visiting Professor for Machine Learning in Health Informatics at Vienna University of Technology; he founded the Expert Network HCI-KDD to foster a synergistic combination of methodologies of two areas that offer ideal conditions toward unraveling problems in understanding complex data: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human intelligence with machine learning for knowledge discovery.

Biography

Andreas Holzinger is lead of the Holzinger Group, head of the Research Unit HCI-KDD at the Institute for Medical Informatics, Statistics and Documentation at the Medical University Graz, and Associate Professor of Applied Computer Science at the Institute of Information Systems and Computer Media at Graz University of Technology. Currently, Andreas is Visiting Professor for Machine Learning in Health Informatics at the Faculty of Informatics at Vienna University of Technology. His research interests are in supporting human intelligence with machine learning to help to solve problems in biomedical informatics and the life sciences. Andreas obtained a Ph.D. in Cognitive Science from Graz University in 1998 and his Habilitation (second Ph.D.) in Computer Science from Graz University of Technology in 2003. Andreas was Visiting Professor in Berlin, Innsbruck, London (2 times), and Aachen. Andreas founded the Expert Network HCI-KDD to foster a synergistic combination of methodologies of two areas that offer ideal conditions toward unraveling problems in understanding complex data: Human-Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human intelligence with machine learning for knowledge discovery. Andreas is Associate Editor of Knowledge and Information Systems (KAIS), and member of IFIP WG 12.9 Computational Intelligence.

Areas of Research / Professional Expertise

    Machine Learning, Health Informatics

Personal Interests

    The goal of the Holzinger Group is to design and develop algorithms which can learn from data and improve with experience over time. However, the application of such automatic machine learning (aML) approaches in the complex health domain seems elusive in the near future, and a good example are Gaussian processes, where aML (e.g. standard kernel machines) struggle on function extrapolation problems which are trivial for human learners.

Websites

Books

Featured Title
 Featured Title - Big Data of Complex Networks - 1st Edition book cover