Publications of Andreas Holzinger in Google Scholar or DBLP

Andreas Holzinger build a solid track record in machine learning/artificial intelligence (see definition) & knowledge extraction for health informatics. Particularly he has been working on integrated machine learning, which is manifested in Holzinger’s HCI-KDD approach. This is based on the idea of combining the best of the two worlds working towards understanding intelligence: Human–Computer Interaction (HCI), rooted in cognitive science, particularly dealing with human intelligence, and Knowledge Discovery/Data Mining (KDD), rooted in computer science, particularly dealing with artificial intelligence. Andreas has pioneered the interactive machine learning approach with the human-in-the-loop. Holzinger proved his concept with his glass-box approach. In light of raising legal and privacy issues in the European Union  (General Data Protection Regulation, GDPR) this will become important – particularly for the health domain. In the future it will become important to make decisions transparent, understandable and retraceable and to explain why a machine decsion has been made – towards explainable artificial intelligence (explainable-ai).

Technical Area: Machine Learning & Knowledge Extraction (MAKE)
Application Area: Health Informatics
Keywords: Explainable AI, interactive Machine Learning (iML), Knowledge Discovery

Publication metrics as of 03.01.2018 12:00 CET:

Google Scholar: Citations: 8900
Google Scholar h-Index: 42
Google Schloar i10-Index: 186
DBLP Peer-reviewed conference papers: 160
DBLP Peer-reviewed journal papers: 65
DBLP Peer-reviewed book chapters: 23
DBLP Edited books and Journal issues: 40
ArXiV contributions: 05

a) 3-pages CV

b) Selected 10 journal publications of the last 5 years

c) Selected Publications of the last 5 years

d) Selected Publications of the last 10 years