Title: TBC

Professor Franco Zambonelli

ACM Distinguished Scientist, Member of the Academia Europaea, Fellow of the Institute of Electrical and Electronics Engineering (IEEE), Fellow of the Asia-Pacific Artificial Intelligence Association (AAIA)
University of Modena and Reggio Emilia, Italy

Short Bio: Franco Zambonelli is full professor of Computer Science at the University of Modena and Reggio Emilia. He got his PhD in Computer Science and Engineering from the University of Bologna in 1997. His research interests include: pervasive computing, multi-agent systems, self-adaptive and self-organizing systems, with applications to healthcare and smart cities. He has published over 130 papers in peer-reviews journals, and has been invited speaker at many conferences and workshops. He is in the editorial board of the ACM Transactions on Autonomous and Adaptive Systems, Springer-Nature Computer Science Journal, IEEE Society and Technology Magazine, the BCS Computer Journal, the Journal of Pervasive Computing and Communications. He has been scientific manager of the EU FP6 Project CASCADAS and coordinator of the EU FP7 Project SAPERE and of the PRIN 2017 Project Fluidware. He is ACM Distinguished Scientist, Member of the Academia Europaea, IEEE Fellow, and has been recipient of the 2018 IFAAMAS Influential Paper Award.

Title: TBC

Professor Cecilia Mascolo

Co-director of Centre for Mobile, Wearable Systems and Augmented Intelligence, Fellow of Jesus College
University of Cambridge, UK

Short Bio: Cecilia Mascolo is the mother of a teenage daughter but also a Full Professor of Mobile Systems in the Department of Computer Science and Technology, University of Cambridge, UK. She is co-director of the Centre for Mobile, Wearable System and Augmented. She is also a Fellow of Jesus College Cambridge and the recipient of an ERC Advanced Research Grant. She has been Deputy Head of Department between 2018 and 2021. Prior joining Cambridge in 2008, she was a faculty member in the Department of Computer Science at University College London. She holds a PhD from the University of Bologna. Her research interests are in mobile systems and machine learning for mobile health. She has published in a number of top tier conferences and journals in the area and her investigator experience spans projects funded by Research Councils and industry. She has served as steering, organizing and programme committee member of mobile and sensor systems, data science and machine learning conferences.

Title: Representation and Quantification of Uncertainty in Machine Learning

Professor Eyke Hüllermeier

Chair of Artificial Intelligence and Machine Learning
Ludwig-Maximilians-Universität München, Germany

Abstract: Due to the steadily increasing relevance of machine learning for practical applications, many of which are coming with safety requirements, the notion of uncertainty has received increasing attention in machine learning research in the recent past. This talk will address questions regarding the representation and adequate handling of (predictive) uncertainty in (supervised) machine learning. A specific focus will be put on the distinction between two important types of uncertainty, often referred to as aleatoric and epistemic, and how to quantify these uncertainties in terms of suitable numerical measures. Roughly speaking, while aleatoric uncertainty is due to randomness inherent in the data generating process, epistemic uncertainty is caused by the learner's ignorance about the true underlying model.

Short Bio: Eyke Hüllermeier is a full professor at the Institute of Informatics at LMU Munich, Germany, where he heads the Chair of Artificial Intelligence and Machine Learning. He studied mathematics and business computing, received his PhD in computer science from Paderborn University in 1997, and a Habilitation degree in 2002. Prior to joining LMU, he held professorships at several other German universities (Dortmund, Magdeburg, Marburg, Paderborn) and spent two years as a Marie Curie fellow at the IRIT in Toulouse (France). His research interests are centered around methods and theoretical foundations of artificial intelligence, with a specific focus on machine learning, preference modeling, and reasoning under uncertainty. Besides, he is interested in the application of AI methods in other disciplines, ranging from the natural sciences and engineering to the humanities and social sciences.

He has published more than 400 articles on related topics in top-tier journals and major international conferences, and several of his contributions have been recognized with scientific awards. Professor Hüllermeier serves on the editorial board of leading journals in AI and machine learning and is a regular member of the program committee of major AI conferences. Currently, he also serves as president of EuADS, the European Association for Data Science.

Title: TBC

Professor Roberto Navigli

Full Professor and Head of the Sapienza NLP Group, Co-founder of Babelscape srl & BabelNet evangelist
Sapienza University of Rome, Italy

Short Bio: Roberto Navigli is a full professor of Natural Language Processing in the Department of Computer, Control and Management Engineering at the Sapienza University of Rome and the head of the Sapienza NLP Group. In 2007 he received a Ph.D. in Computer Science from "La Sapienza" (winner of the Marco Cadoli 2007 AI*IA prize for the Best Ph.D. Thesis in AI). In 2013 he received the Marco Somalvico AI*IA prize, awarded to the best young Italian researcher in AI, who has provided a significant, highly-innovative personal contribution in AI.