[DL] Spotlight Seminar on AI - MICHELA MILANO - May 19

[Chiara Ghidini]

[* Apologies in case of multiple posting *]

The Italian Association for Artificial Intelligence is pleased to announce the next seminar of its Spotlight Seminars on AI initiative:

May, 19 – 5:00PM (CEST)
Title: Integrating Learning, Optimization and Reasoning
Speaker: MICHELA MILANO, Università di Bologna

The aim of the seminar series is to illustrate, explore and discuss current scientific challenges, trends, and possibilities in all branches of our articulated research field. The seminars will be held virtually on the YouTube channel of the Association (https://www.youtube.com/c/AIxIAit), on a monthly basis (and made permanently available on that channel), by leading Italian researchers as well as by top international scientists. 

The seminars are mainly aimed at a broad audience interested in AI research, and they are also included in the Italian PhD programme in Artificial Intelligence; indeed, AIxIA warmly encourages the attendance of young scientists and PhD students. 

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Bio: Michela Milano is full professor of Artificial Intelligence at DISI – University of Bologna and she chairs the interdepartmental Institute of Human-Centered Artificial Intelligence counting 27 Departments and more than 400 researchers. She is past Deputy President of the European Association of Artificial Intelligence (EurAI) and past Executive Councilor of the Association for the Advancements of Artificial Intelligence (AAAI), past member of the Executive Committee of the Association for Constraint Programming and of the Italian Association of Artificial Intelligence. Her research activity concerns Artificial Intelligence with particular focus on decision support and optimization systems. In this field Michela Milano has written more than 170 papers on peer reviewed international conferences and journals.  She coordinated many European scientific and industrial projects. 

Abstract: In the last decade we have seen a surge in methods that merge learning, optimization and reasoning. The main motivation behind this line of research comes from the need to produce decision models merging data-driven and knowledge-based components. The interaction between these methods can be obtained in two directions: the former relies on the integration of machine learning models into optimization or decision support tools, the latter is based on the injection of domain knowledge coming from human experts into machine learning models. In the talk two approaches will be presented along with a discussion on use cases that benefit from the integration.

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The Spotlight Seminars on AI Committee, 
Giuseppe De Giacomo
Chiara Ghidini
Gianluigi Greco
Marco Maratea
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