CS Colloquium Series @ UCY

Department of Computer Science - University of Cyprus

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Colloquium Coordinator: Demetris Zeinalipour

Colloquium: Artificial Intelligence Research for Real World Challenges, Prof. Grigoris Antoniou (University of Huddersfield, UK), Tuesday, November 26, 2019, 11:00-12:00 EET.


The Department of Computer Science at the University of Cyprus cordially invites you to the Colloquium entitled:

Artificial Intelligence Research for Real World Challenges

 

Speaker: Prof. Grigoris Antoniou
Affiliation: University of Huddersfield, UK
Category: Colloquium
Location: Room 148, Faculty of Pure and Applied Sciences (FST-01), 1 University Avenue, 2109 Nicosia, Cyprus (directions)
Date: Tuesday, November 26, 2019
Time: 11:00-12:00 EET
Host: Prof. Elpida Keravnou Papailiou (elpida-AT-cs.ucy.ac.cy)
URL: https://www.cs.ucy.ac.cy/colloquium/index.php#cs.ucy.2019.antoniou

Abstract:
Data originating from the Web, sensor networks and social media result in increasingly huge datasets. The so called Big Data creates new opportunities for advanced applications in domains ranging from smart cities to intelligent healthcare, hence the increasing interest in academia and industry. Usually Big Data is associated with machine learning/data mining. This talk will argue that semantic and knowledge technologies have an important role to play. Traditionally, reasoning approaches have mostly focused on complex knowledge structures/programs and centralized in-memory data, so the question arises whether and how they can be adapted to scale sufficiently to meet the Big Data challenges. A number of open research challenges in the area will be discussed, as well as possible applications in the legal domain. Then we will turn our attention to the area of mental health, a key healthcare challenge in worldwide. We will present results around applying machine learning to two specific areas of mental health: assessment of suicide risk, and diagnosis of ADHD in adults. In close collaboration with domain experts, relevant clinical data was analysed to develop predictive models. In contrast to most works of applying AI to healthcare (a) we relied on clinical data currently collected, so as not to increase the burden on healthcare systems; (b) we developed locally adapted models as clinical decision making may be different in London, Brisbane or Nicosia in view of geographical, social and cultural differences. Issues around explainability will also be discussed.

Short Bio:
Grigoris Antoniou is Professor of Computer Science at the University of Huddersfield, UK. Previously he has held professorial appointments at the University of Crete (where he was also Head of the Information Systems Laboratory at FORTH-ICS, the top-rated research institute in Greece), Griffith University, Australia, and the University of Bremen, Germany. His research interests lie in semantic technologies, particularly knowledge representation and reasoning and semantics for big data, and its application to ambient intelligence, e-health, and transportation. He has published over 200 technical papers in scientific journals and conferences. He is author of three books with international publishers (MIT Press, Addison-Wesley); his book "A Semantic Web Primer" is internationally the standard textbook in the area, and has been translated to Japanese, Chinese, Korean, Spanish and Greek. His research has attracted over 10.000 citations. He is member of editorial boards of journals including Artificial Intelligence Journal, has organised a number of conferences and workshops (including leadership positions at ESWC 2010 and 2011), and has served in numerous programme committees. He has led a number of national and international research projects, and has participated in many more. He is Fellow of the European Association for Artificial Intelligence.

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