Keynote Speaker
Katrien Verbert - KU Leuven
Explaining job recommendations: a human-centred perspective
Katrien Verbert is Associate Professor at the Augment research group of KU Leuven. She obtained a doctoral degree in Computer Science in 2008 at KU Leuven, Belgium. She was a postdoctoral researcher of the Research Foundation – Flanders (FWO) at KU Leuven. She was an Assistant Professor at TU Eindhoven, the Netherlands (2013 –2014) and Vrije Universiteit Brussel, Belgium (2014 – 2015). Her research interests include visualisation techniques, recommender systems, explainable AI, and visual analytics. She has been involved in several European and Flemish projects on these topics, including the EU ROLE, STELLAR, STELA, ABLE, LALA, PERSFO, Smart Tags and BigDataGrapes projects. She is also involved in the organisation of several conferences and workshops (general co-chair IUI 2021, program chair LAK 2020, general chair EC-TEL 2017, program chair EC-TEL 2016, workshop chair EDM 2015, program chair LAK 2013 and program co-chair of the EdRecSys, VISLA and XLA workshop series, DC chair IUI 2017, DC chair LAK 2019).
Michele Sebag - CNRS and University Paris-Saclay
Discussing Machine Learning and Economic Views on Job Recommendation
Michele Sebag is a senior researcher at CNRS and Univ. Paris-Saclay. With a background in Maths, she went to industry, then entered the French National Center for Research (CNRS). She is head of the Machine Learning and Optimization team in the Lab of Interdisciplinary Computer Science at Université Paris-Saclay, and co-head with Marc Schoenauer of the Inria team TAU, (Tackling the Underspecified - referring to the number of under-specified issues at the core of Artificial Intelligence). Her research interests include causal modelling, deep learning, and applications of machine learning for society (health, hiring, social sciences). She was elected European AI Fellow and member of the French Academy of Technology.