Austria is the country with the highest number of top (female) RecSys researchers
We updated our world map of the top recommender-systems researchers, i.e. researchers on the RecSys Steering Committee, or RecSys researchers otherwise strongly involved in the community. Among others, we updated the location of Christine Bauer who moved from Utrecht University (Netherlands) to Salzburg University (Austria). Given the relatively small size of Austria and the relatively small number of universities, it is amazing to see how many top recommender-systems researchers there are in Austria.
Based on our numbers, Austria is the country with the highest number of professors and top recommender-systems researchers in the world, relative to the number of universities. And, the most female, too.
The list includes
- Dietmar Jannach, University of Klagenfurt
- Markus Zanker, University of Klagenfurt (and University of Bolzano)
- Alexander Felfernig, University of Graz
- Elisabeth Lex, University of Graz
- Christine Bauer, University of Salzburg
- Eva Zangerle, University of Innsbruck
- Julia Neidhardt, University of Vienna
- Markus Schedl, University of Linz
‘Recsperts’ releases its 20th episode; This time on Practical Bandids and Travel Recommendations
Dietmar Jannach is featured by “People of ACM”
Joseph (‘Joe’) A. Konstan runs for the ACM presidency
About The Author
Joeran Beel
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries. We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).