7th Int'l Summer School on Data Science (SSDS 2022) will be organized online!
Day 1 - Monday, 10 October 2022
9:00-9:15 Welcome and introduction to summer school (Direct link to session)
Sven Lončarić, Faculty of Electrical Engineering and Computing, University of Zagreb
Tomislav Šmuc, Ruđer Bošković Institute, Zagreb, Croatia
9:15-10:45 Explainability in AI I: Introduction (Direct link to session)
Wojciech Samek, Head of AI Department, Fraunhofer HHI, Professor of machine learning and communications, TU Berlin, Germany
10:45-11:00 Break
11:00-12:30 Explainability in AI II: Advanced methods (Direct link to session)
Wojciech Samek, Head of AI Department, Fraunhofer HHI, Professor of machine learning and communications, TU Berlin, Germany
12:30-13:30 Break
13:30-15:00 Hands-on session: Explainability in AI (Direct link to session)
Anna Hedström and Christopher Anders, TU Berlin, Germany
Day 2 - Tuesday, 11 October 2022
11:00-13:00 XAI-Enabled Applications for Healthcare Scenarios (Direct link to session)
Salvatore Rinzivillo, Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)
16:30-18:00 The Relationship between Explainability & Privacy in AI (Direct link to session)
Anna Monreale, Associate Professor, Computer Science Department of the University of Pisa, Italy
Day 3 - Wednesday, 12 October 2022
09:00-10:30 Modelling Causality with Causal Graphs - (The lecture is canceled due to illness)
Sofia Triantafillou, Assistant Professor, Department of Mathematics and Applied Mathematics, University of Crete, Greece
10:30-10:45 Break
10:45-12:15 Learning Causal Graphs from Data (The lecture is canceled due to illness)
Sofia Triantafillou, Assistant Professor, Department of Mathematics and Applied Mathematics, University of Crete, Greece
12:15-13:30 Break
13:30-15:00 Hands-on session: Learning and modeling with Causal graphs (The lecture is canceled due to illness)
Miha Keber, Machine Learning and Knowledge Representation Lab, Rudjer Boskovic Institute, Zagreb, Croatia.
Day 4 - Thursday, 13 October 2022
09:00-10:30 Causality for Machine Learning I (Direct link to session)
Matej Zečević, PhD Candidate, Machine Learning Group, Computer Science Department, TU Darmstadt, Germany
10:30-10:45 Break
10:45-12:15 Causality for Machine Learning II (Direct link to session)
Matej Zečević, PhD Candidate, Machine Learning Group, Computer Science Department, TU Darmstadt, Germany
12:15-13:30 Break
13:30-15:00 Hands-on session: Causality for Machine Learning (Direct link to session)
Matej Zečević, PhD Candidate, Machine Learning Group, Computer Science Department, TU Darmstadt, Germany
15:00-17:00 Break
17:00-18:30 Methods and Tools for Causal Discovery (Direct link to session)
Rita Nogueira, PhD Candidate, Researcher at LIAAD - INESC TEC, Porto, Portugal
Day 5 - Friday, 14 October 2022
09:00-10:30 Learning Explainable Models of Dynamic Systems I (Direct link to session)
Sašo Džeroski, Head, Department of Knowledge Technologies, Josef Stefan Institute, Ljubljana, Slovenia
10:30-10:45 Break
10:45-12:15 Learning Explainable Models of Dynamic Systems II (Direct link to session)
Sašo Džeroski, Head, Department of Knowledge Technologies, Josef Stefan Institute, Ljubljana, Slovenia
12:15-13:30 Break
13:30-14:30 Modelling Causality with Causal Graphs (Direct link to session)
Sofia Triantafillou, Assistant Professor, Department of Mathematics and Applied Mathematics, University of Crete, Greece
14:30-14:45 Break
14:45-15:45 Learning Causal Graphs from Data (Direct link to session)
Sofia Triantafillou, Assistant Professor, Department of Mathematics and Applied Mathematics, University of Crete, Greece