New date for paper submissions (only for workshops): July 20, 2024
Responsible Artificial Intelligence (ReAI)
Description:
Research in AI promises to bring huge advances in all aspects of human life from groundbreaking discoveries in medicine and self-driving cars to the arts. But it also raises important ethical concerns.
The goal of the ReAI workshop is to bring together researchers and practitioners in the broad area of responsible AI to discuss recent advancements and future perspectives of this rapidly changing field. Special emphasis will be placed on how Greece is tackling these challenges aiming at fostering a community on the topic of responsible AI.
The workshop will focus on the foundations, principles, and practices of developing AI systems responsibly, addressing issues of fair and unbiased treatment, explainability, accountability, transparency, privacy, safety, and truthfulness. Besides covering technical aspects, the workshop will also provide a broader interdisciplinary perspective by addressing legal, social, and ethical perspectives.
Topics to be covered include but are not limited to:
– Bias and fairness in AI systems,– Transparency, interpretability and explainability (XAI),
– AI regulations,
– Privacy and accountability,
– Use cases.
Organizers
Evaggelia Pitoura, University of Ioannina and Archimedes AI RU, Greece
Lilian Mitrou, University of the Aegean, Greece
Eirini Ntoutsi, University of the Bundeswehr Munich, Germany
Danae Pla Karidi, Archimedes AI RU, Greece.
For additional information including submission instructions please visit the workshop webpage at: https://reai24.github.io/ReAI/
AI-Driven Knowledge Graph Construction (AIKGC)
Description:
In an era where data (either unstructured, semi-structured or structured) is not just abundant but also the bedrock of innovation, knowledge graphs stand out as pivotal tools for structuring this data, making it interpretable and actionable by AI systems. They enable the representation of data in a form that mirrors human understanding, facilitating more natural interaction between humans and machines, and enhancing AI’s ability to generate insights that are both deep and relevant. The construction of knowledge graphs embodies the synthesis of various AI disciplines, including natural language processing, machine learning, and semantic web technologies. This workshop aims to foster a collaborative environment where experts and enthusiasts across these fields can converge to share insights, challenges, and breakthroughs. This convergence is crucial for pushing the boundaries of what AI can achieve, making it more adaptable, intuitive, and capable of handling the nuances of real-world information. By bridging the gap between theoretical research and practical applications, the objective is to accelerate the integration of Knowledge Graphs into diverse domains, from healthcare to cybersecurity, enhancing decision-making processes and creating more intelligent, autonomous systems.
This workshop is supported by the ENCRYPT project (https://encrypt-project.eu/) which aims to tackle privacy and security challenges in critical sectors such as healthcare, finance, and entertainment, driven by the expansion in digital data. In this context, Knowledge Graphs are used to introduce a semantic layer on top of the available data relevant to the use cases, with the aim of interlinking and contextually enriching the schemata and data in an interoperable manner.
Specific topics covered and possible application areas:
This workshop targets a wide range of topics covered related to knowledge graphs, as well as several application areas. An indicative list is as follows:
Topics
– Foundations of Knowledge Graphs,
– Knowledge Graphs and Semantic Web Technologies,
– Knowledge Extraction and Integration,
– Machine Learning, Large Language Models and Knowledge Graphs,
– Generative Knowledge Graph Construction,
– Natural Language Processing (NLP) for Knowledge Graphs,
– Knowledge Graph Construction Tools and Technologies,
– Scalability and Performance Optimization.
Application areas
– Healthcare and Life Sciences,
– Security and Cybersecurity,
– Finance and Economics,
– Human-computer interaction / Conversational agents,
– E-Commerce, Retail and Consumer Packaged Goods,
– Smart Cities and IoT,
– Cultural Heritage and Digital Humanities,
– Environmental Science and Sustainability.
Organizing Committee
Maria Papoutsoglou, School of Informatics, Aristotle University of Thessaloniki
Georgios Meditskos, School of Informatics, Aristotle University of Thessaloniki
Nick Bassiliades, School of Informatics, Aristotle University of Thessaloniki
Efstratios Kontopoulos, Foodpairing AI
Stefanos Vrochidis, Information Technologies Institute, CERTH
Contact person: Maria Papoutsoglou (email: mpapo@csd.auth.gr)
Workshop webpage: https://aikgc2024.csd.auth.gr/
AI for Fashion
Description:
Following the success of the 1st Workshop on AI4Fashion hosted by the 11th SETN2020 & 2nd Workshop hosted by the 12th SETN2022, we would like to continue the event inviting more people to participate. Even though AI has been around for several years now, the technologies that are currently being applied to fashion are still in its early days. The goal of this workshop is to gather people from academia, industry, and startups working at the intersection of fashion and data mining, processing, AI resonance and knowledge discovery, to further advance the technology and its adoption. This 3rd instalment of the workshop can become, in the future, the premier venue for presenting works that are solving problems related to fashion using artificial intelligence, machine learning and data mining.
TopicsOrganizers of this workshop understand the need for bridging the gap of the current state of art in fashion and the new technological advancements in AI and Big Data and, thus, aim to bring together all the researchers, practitioners, and stakeholders from fashion industry to explore the open problems, applications, and future directions in this field. We believe that the fashion industry introduces a number of interesting data analytics problems that are either not studied or scarcely studied in the past and can attract great interest in the general SETN community given their practical implications.
Suggested topics include (but not limited to):– Detect and forecast fashion trends and cycles,
– AI tools for fashion designers,
– Creative AI for fashion,
– Personal styling with humans and machines: recommendations with humans in the loop,
– Assembling outfit recommendations: interactions and serendipity,
– Algorithmic clothing: design by data,
– Predicting fashionability scores,
– Social networking for fashion,
– Fashion retail analytics,
– Big data for fast fashion,
– Deep learning for fashion,
– Augmented and Virtual reality for clothes virtual try on,
– Learning-based clothes recognition and categorization,
– Real-time state tracking for garments and clothes,
– Modeling and simulation tools for clothing,
– Visual search for fashion e-commerce,
– Fashion image understanding and auto-tagging of apparel,
– Novel search mechanisms for large fashion catalogs,
– Virtual personal fashion assistants,
– Recommendation engines and cognitive stylists for fashion,
– Fashion retail analytics.
Organizing Committee
Evridiki Papachristou, School of Design Science, Department of Creative Design & Clothing, International Hellenic University
Giorgos Stamou, School of Electrical and Computer Engineering, NTUA
Theodoros Kostoulas, Department of Information and Communication Systems Engineering, Universityy of the Aegean
Contact person: Evridiki Papachristou (email: evridikipapa@ihu.gr)
AI in Natural Sciences and Technology (AINST)
Description:
Artificial Intelligence (AI) tends to become a horizontal infrastructure, supporting a variety of disciplines and applications. During the last few years a number of works highlight the potential of AI utilization in natural science settings and the potential for cross-fertilization between disciplines. In SETN 2022 the AI in Natural Sciences and Technology workshop was particularly successful, drawing more than 18 submissions.
The workshop aims to bring together AI and:
– Mathematical modeling,
– Physics,
– Chemistry,
– Materials science and engineering,
– Biology and biomedical engineering,
– Pharmaceutical applications and bioinformatics,
– Environmental science and engineering,
– Weather and climate forecasting,
– Nanotechnology,
– Big, experimental data analyses and Cloud Computing (e.g. genomic data, particle physics).
Topics
– Adapting AI for natural sciences and engineering,
– Molecular modeling and simulation of materials and processes,
– Big, experimental data analyses (e.g. genomic data, particle physics),
– New materials design,
– Optimization of technological and industrial processes,
– Microscopy enhancement (Deep Learning Microscopy),
– Challenges of AI in natural sciences use cases,
– Quantum computation and AI,
– Error correction and noise removal.
Organizing Committee
George Giannakopoulos, NCSR “Demokritos” and SciFY PNPC, Greece
Vassilios Constantoudis, Institute of Nanoscience and Nanotechnology, NCSR “Demokritos”, Greece
Niki Vergadou, Institute of Nanoscience and Nanotechnology, NCSR “Demokritos”, Greece
Panagiotis Dimitrakis, Institute of Quantum Computing, NCSR “Demokritos”, Greece
Stelios Karozis, NCSR “Demokritos”, Greece
Christoforos Rekatsinas, NCSR “Demokritos”, Greece
Panagiotis Krokidas, NCSR “Demokritos”
Contact person: Christoforos Rekatsinas, crek@iit.demokritos.gr
For further information about this edition of the workshop please visit the AINST Website.
Cognitive Robotics: A workshop
Description:
The field of Cognitive Robotics is experiencing an unprecedented growth in our days. Because an intelligent robot is a physically situated intelligent agent, the tools and techniques for designing purposive, intelligent and adaptive capabilities in robots has a significant overlap with the methodologies and approaches of Artificial Intelligence (AI). These range from the older symbolic mechanisms on knowledge representations, reasoning and planning to the current techniques on reinforcement learning, transformers and Large Language Models. This field of combining AI and Robotics is referred to as “Intelligent Robotics”, or “Robotics & AI” or “Cognitive Robotics”. As defined in the 1998 AAAI Winter Workshops, Cognitive Robotics is “concerned with integrating reasoning, perception and action within a uniform theoretical and implementation framework”. Cangelosi and Asada in the recent book Cognitive Robotics define the field as one that combines insights and methods from AI, as well as cognitive and biological sciences, to robotics.
Content:– Cognitive robotics is one of the fastest-growing sub-fields of robotics. This has piqued the interest of roboticists worldwide, resulting in a cascade of papers with applications varying over a wide span, including domestic, search and rescue, and medical to mention a few. In this spirit, we will invite original research papers on topics including (but not limited to) the following:
– Robots that find objects
– robots that understand spatial relations
– robots that learn to detect object attributes and affordances
– robots that understand natural language and carry out commands
– conversational robots (if they don’t understand the command, they can ask a question for clarification)
– robots that answer questions about scenes
– robots that learn from observation
– robots that recognize actions
– robots that predict the next event
– robots that learn to perform very large numbers of tasks, semantic navigation
– robots learning assembly tasks
– robots understand human emotional states
– social robots inferring intentions
– the usage of LLMs in cognitive robot planning
– etc.
– The scope of this all-day workshop is to gather researchers from different research areas across several sections.
This way, we will range the discussion from previously experienced problems to contemporary solutions, while focusing on the future trends that remain an open problem in the community. Talks from high recognized scholars/researchers in the field and questions and answers during the workshop session would permit the participation of the audience with the pioneers. Furthermore, we will host a poster session where the young and upcoming participants in the field will be able to interact with esteemed scholars, thereby exchanging ideas and further enhancing their research philosophies.
– We are currently exploring the possibility of a journal special issue for the best contributions to the workshop.
Yiannis Aloimonos, Professor, Primary contact person
Affiliation: University of Maryland, College Park
Address: 8125 Paint Branch Drive, College Park, MD 20740, USA
Phone: +1 301 405-174
Email: jyaloimo@umd.edu
URL: http://prg.cs.umd.edu/
Antonios Gasteratos, Professor
Affiliation: Democritus University of Thrace
Address: Vas. Sophias 12, 671 00 Xanthi, Greece
Phone: +30 25410 79359
Email: gaster@pme.duth.gr
URL: http://robotics.pme.duth.gr/antonis/
Antonios Argyros, Professor
Affiliation: University of Crete
Address: Voutes Campus, 700 13 Heraklion Crete, Greece
Phone: + 30 2810 393502
Email: argyros@csd.uoc.gr
URL: https://users.ics.forth.gr/~argyros/
Katerina Pastra, Senior Researcher
Affiliation: Athena Research Center
Address: Artemidos 6 & Epidavrou, 15125 Marousi, Greece
Phone: +30 210 6875430
Email: kpastra@athenarc.gr
URL: https://www.imsi.athenarc.gr/en/people/member/73/
Konstantinos A. Tsintotas, Post-doctoral Researcher
Affiliation: Democritus University of Thrace
Address: Vas. Sophias 12, 671 00 Xanthi, Greece
Phone: +30 25410 79330
Email: ktsintot@pme.duth.gr
URL: https://robotics.pme.duth.gr/ktsintotas
For further information about the workshop please visit the website https://robotics.pme.duth.gr/workshop_cogrob/