CLAIRE | Rising Research Network: AI Research and Mental Well-Being Workshop 2nd edition

Marie Anastacio PhD candidate at Leiden University, RWTH Aachen After the successful execution of our 2023 workshop in collaboration with the TAILOR-ESSAI Summer School, we propose to organise a second edition at ESSAI2024. The event will focus on fostering a community of young AI researchers in Europe, supporting AI researchers and promoting mental well-being for […]

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Machine Learning Modalities for Materials Science

Milica Todorovic Associate professor at University of Turku In the past decade, artificial intelligence algorithms have demonstrated a tremendous potential and impact in speeding up the processing, optimisation, and discovery of new materials. The objective of the workshop and school “Machine Learning Modalities for Materials Science” (MLM4MS 2024) was to bring together the community of

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Evaluating the Trustworthiness of Human-like Robotic Motion

Filipa Correia Assistant Researcher at Interactive Technologies Institute, University of Lisbon The research project will explore the trustworthiness of an embodied AI, such as a social robot. Specifically, it will investigate whether the performance of humanlike motions of a non-humanoid robot enhances the perceived trustworthiness of that robot. Beyond the scientific contribution to the current

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Explanations and Reasoning: Proofs and Models of Intuitionistic Modal Logics

Philippe Balbiani CNRS researcher at Toulouse Institute of Computer Science Research (Toulouse, France) Rooted in Intuitionistic and Constructive Reasoning, Intermediate Logics have found important applications through the Curry-Howard correspondence. Nowadays, there is an Intuitionistic Modal Logics renaissance in Computer Science and Artificial Intelligence. Connections between, on one hand, Intuitionistic and Constructive Mathematics and, on the

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Neuro-symbolic integration for graph data

Manfred Jaeger Associate Professor at Aalborg University Learning and reasoning with graph and network data has developed as an area of increasing importance over recent years. Social networks, knowledge graphs, sensor and traffic networks are only some of the examples where graph-structured data arises in important applications. Much of the attention currently focuses on graph

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Improving Cross-Lingual Retrieval of Previously Fact-Checked Claims

Róbert Móro Researcher at Kempelen Institute of Intelligent Technologies To mitigate disinformation with AI in a trustworthy way, it should prioritize human agency and control, transparency, and accountability including the means for redress. This can be achieved by using AI to support rather than to replace media professionals, such as fact-checkers, in their efforts to

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Enhancing Reliability and Trustworthiness in IoT Applications through Deep Learning-Based Data Imputation Techniques

Hakob Grigoryan PhD at NVISION With the evolution of intelligent sensing devices and the Internet of Things (IoT), a vast amount of data is generated from various sources, including sensors, cameras, and network infrastructures, and is transmitted to servers for analysis. Data streaming from sensors in IoT systems might face quality issues like incompleteness due

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Exploring Intrusion Detection Knowledge Transfer Between Network Environments

Patrik Goldschmidt PhD candidate at Kempelen Institute of Intelligent Technologies With the rise of information technology and the Internet, the number of cybersecurity incidents has grown immensely. As a response, the research area of Intrusion Detection Systems (IDSs), aiming to detect and mitigate cyber threats, has gained significant attention. Our research focuses on Network IDSs

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Keynote by Rao

Subbarao “Rao” Kambhampati, professor of computer science at Arizona State University, will give a keynote lecture at the 4th TAILOR conference “Trustworthy AI from Lab to market”, 4-5 June 2024, Lisbon. His talk will be about the role of LLM:s in planning tasks.

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