Publications of Andreas Holzinger in Google Scholar or DBLP

Andreas Holzinger build a solid track record in AI/machine learning (see definition) for health informatics always with a strong focus on research-based teaching. Andreas 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 two worlds 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. Particularly, Andreas has pioneered the interactive machine learning approach with a human-in-the-loop. Holzinger proved his concept with his glass-box approach, which will become important in the future due to raising legal and privacy issues in the European Union  – particularly for the health informatics domain. Moreover, 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) – ex-AI.

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

Publication metrics as of 18.04.2018 09:00 CEST:

Google Scholar: Citations: 9430
Google Scholar h-Index: 43
Google Schloar i10-Index: 190
DBLP Peer-reviewed conference papers: 163
DBLP Peer-reviewed journal papers: 66
DBLP Peer-reviewed book chapters: 23
DBLP Edited books and Journal issues: 40
ArXiV contributions: 12

a) 3-pages CV

b) Selected 10 original journal publications of the last 5 years

c) HOLZINGER-Publications-last-five-years

d) 5-pages research statement

e) 5-pages teaching statement

f) 3-minutes Video statement “MAKE”

g) 20-minutes Video statement “Welcome to students”