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ForgtAI : International Workshop on Forging Trust in Artificial Intelligence -- DEADLINE EXTENDED to 27/03/2025

Establishing and upholding trust in AI systems is an imperative pursuit as Machine Learning becomes an everyday commodity in our lives. The workshop “Forging Trust in Artificial Intelligence” brings together a group of experts and researchers from diverse subfields, converging on the exploration of how transparency, explainability, fairness, and privacy collectively contribute to making machine learning trustworthy. By uniting experts across these pivotal disciplines, this workshop illuminates the best practices that not only enhance the trustworthiness of AI but also reinforce its ethical foundations. Building on the success of the last year’s workshop, which focused on explainability and security in vision AI, this year’s event shifts its attention to the challenges of managing sequential and multimodal data in NLP and IoT. These areas are at the forefront of human-AI interaction: large language models (LLMs) already shape how we access information and make decisions, while smart IoT systems increasingly define automated processes that directly affect not only the industry but also our everyday lives.

This year’s workshop highlights explainability as a cornerstone of trustworthy AI in continuous systems. It tackles the complexities of understanding how neural networks operate, from demystifying the outputs of LLMs to clarifying automated decisions in continuous IoT environments, and eventually providing more tools to improving AI performance. Ensuring fairness and mitigating biases are also central themes, as these systems increasingly influence critical aspects of human life. By focusing on transparency and ethical practices, the ForgAI Workshop seeks to equip participants with actionable insights and methodologies for building AI systems that inspire confidence and align with societal values. By aligning with IJCNN’s mission to explore the latest advancements in neural networks, the workshop deepens the conversation around responsible AI development. It emphasizes that explainability is not just a technical challenge but a fundamental requirement for creating AI systems that serve as reliable and ethical partners in human-AI interactions.

The following list includes (but is not limited to) relevant topics that will be addressed within this workshop:

Explainability in ML and NLP Models

Explainability in AIoT (Artificial Intelligence in IoT)

Algorithmic Fairness in Machine Learning


Invited Speakers

Professor Vassilis Christophides, ENSEA/ETIS, France
Short Bio:TBA
Invited Talk Title: Towards Explainable-by-design Detection of Bugs in IID and Sequence Datasets
Summary: Traditional ML models are trained under the assumption of finite, closed collections of high quality data. However, in real applications (e.g., in IoT), the statistical properties of the serving data may differ from those used for training, while various forms of data imperfections may slip on the labels or the input features. Clearly, such data bugs degrade the performance of models and jeopardize the reliability of their outcomes. In this presentation, we will introduce an explainable-by-design framework allowing us to detect and explain several types of data bugs by exploiting the influence of samples in the decision boundary of a model. We argue that mislabeled, anomalous, drifted or even poisoned samples have different influence signatures compared to clean samples. We are then proposing several influence-based signals for identifying fine-grained forms of data bugs in IID and sequence datasets. Extensive experiments on various classification tasks demonstrate that our signals are robust across foundation models or models trained from scratch as well as different data modalities (image and tabular datasets).


Professor Anastasios Tefas, Aristotle University of Thessaloniki, Greece
Short Bio: Anastasios Tefas received the B.Sc. in informatics in 1997 and the Ph.D. degree in informatics in 2002, both from the Aristotle University of Thessaloniki, Greece. Since 2022 he has been a Professor at the Department of Informatics, Aristotle University of Thessaloniki. From 2008 to 2022, he was a Lecturer, Assistant Professor, Associate Professor at the same University. He is the director of the MSc program on Artificial Intelligence in the Dept. of Informatics. Prof. Tefas coordinated 16 and participated in 20 research projects financed by national, private and European funds. He was the Coordinator of the H2020 project OpenDR, “Open Deep Learning Toolkit for Robotics”. He has co-authored 160 journal papers, 300 papers in international conferences and contributed 17 chapters to edited books in his area of expertise. He has co-organized more than 15 workshops, tutorials, special sessions, and special issues and has given more than 20 invited talks. He has co-edited the book “Deep Learning for Robot Perception and Cognition”, Elsevier, 2022. Over 13000 citations have been recorded to his publications and his H-index is 55 according to Google scholar. His current research interests include computational intelligence, deep learning, machine learning, data analysis and retrieval, computer vision, autonomous systems and robotics.
Invited Talk Title: Trustworthiness in AI and Autonomous Systems
Summary:TBA


Paper Submission

We accept full or short paper submissions. Full paper submissions (up to 8 pages) will be considered for publication in the IJCNN 2025 proceedings on the IEEE Xplore Digital Library, and will be oraly presented during the workshop. Full papers must follow the same author guidelines (check here) as the papers of the main conference (double blind), and will be reviewed by 3 reviwers of our program committee. Short papers and extended abstracts (up to 4 pages) will be considered for oral presentations or poster presentations at the workshop; however, these will not be included in the proceedings. Papers must be submitted through the IJCNN 2025 CMT System, by selecting the workshop name ‘International Workshop on Forging Trust in Artificial Intelligence 2025’ in the Subject Area.

Submission Deadline: 20/03/2025 27/03/2025

Acceptance Notification: 15/04/2025


Organisers

Alexandros Iosifidis, Tampere University, Finland
Nistor Grozavu, Cergy Paris University/ETIS, France
Aikaterini Tzompanaki, Cergy Paris University/ETIS, France
Corina Besliu, Technical University of Moldova, Moldova
Nicoleta Rogovschi, Paris Descartes University, France


Program Committee

Hajer Baazaoui, CY Cergy Paris University/ETIS, France
Georgios Bouloukakis, Télécom SudParis/IP-Paris, France
Luis Galárraga, INRIA/IRISA, France
Apostolos Giannoulidis, Aristotle University of Thessaloniki, Greece
Michele Linardi,CY Cergy Paris University/ETIS, France
Illia Oleksiienko, Aarhus University, Denmark
Marina Papatriantafillou, Chalmers University of Technology, Sweden
Nikolaos Passalis, Aristotle University of Thessaloniki, Greece
Dimitris Sacharidis, Université Libre de Bruxelles, Belgium
Konstantinos Stefanidis, Tampere University, Finland


Sponsors

The workshop is organised under the support of the PANDORA European project and the german company OTRS GmbH.


Contact: aikaterini.tzompanaki@cyu.fr ; corina.besliu@ati.utm.md