About

Univ.-Prof. Dr. Elisabeth Lex is a full professor at Graz University of Technology (TUG). She is an ELLIS scholar and affiliated with the ELLIS unit Graz. At TU Graz, Elisabeth serves as the dean of study for the master’s program Computational Social Systems. She has a habilitation (venia docendi) in Applied Computer Science, and her postdoctoral thesis is on “Modeling and Predicting User Behavior in Web-based Systems”. Her areas of expertise include machine learning with a particular focus on recommender systems and information retrieval, data science, user modeling, HCI, and inclusive technologies. Elisabeth Lex received her Ph.D. in Computer Science from Graz University of Technology in 2011. After completing the Ph.D. program, she was a postdoctoral research fellow at Universidad National de San Luis, Argentina, and RWTH Aachen, Germany. Elisabeth was a work package leader in the FP7 IP Learning Layers project, in which she researched cognition-informed recommender systems and task leader in the H2020 Analytics for Everyday Learning (AFEL) project, in which she researched psychology-informed recommender systems. Elisabeth was a member of the Expert Group on Altmetrics, which advised the European Commission, DG Research and Innovation. The expert group developed policies for the commission on how to use altmetrics to assess the impact of scientific artifacts. She has published more than 160 scientific publications in venues such as ACM WebConf, RecSys, UMAP, ECIR, ISMIR, as well as in journals such as Foundations and Trends in Information Retrieval, UMUAI, EPJ Data Science, Frontiers in AI, Transactions of the International Society for Music Information Retrieval (TISMIR), or the International Journal of Human-Computer Interaction. Elisabeth regularly gives invited talks about her research and acts as Senior PC member, PC member, co-organizer, track chair, and co-track chair at venues such as RecSys, UMAP, WebConf, IUI, Web Science, or HT. Elisabeth is a passionate teacher at TU Graz, where she teaches Advanced Information Retrieval, Recommender Systems and Computational Methods for Statistics, among other courses.