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CALL FOR PAPERS
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iwAIIS2026 – 1st International Workshop on Artificial Intelligence and Intelligent Systems
Marina Bay Sands Hotel, Singapore | Hybrid | Open-access publication
December 8–9, 2026
Workshop website: https://www.iwaiis.org/
Submission link: https://meteor.springer.com/iwAIIS_2026
Held in conjunction with 8th icSoftComp2026 (https://icsoftcomp.org/)
Conference series link: https://link.springer.com/conference/icsoftcomp
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Important notes:
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– Open-access publication
– Workshop proceedings by Springer CCIS Series (Scopus-indexed)
– Best Research Paper & Best Student Paper Awards
– iwAIIS 2026 follows a double-blind peer review system.
– The workshop will be held in a hybrid mode: onsite and online.
– Authors of selected papers will be invited to submit extended article versions for a post-conference special issue of peer-reviewed Scopus-indexed journals.
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Submission Deadline:
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Sep 15, 2026 (AoE) Firm Deadline.
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Venue:
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Marina Bay Sands Hotel, Singapore
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Indexing:
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Scopus, Google Scholar, DBLP, Ei Compendex, and Springerlink
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Keynote Speakers:
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– Lipo Wang, Nanyang Technological University, Singapore
– Jochen Wirtz, National University of Singapore (NUS), Singapore
– Kay Romer, TU Graz, Graz University of Technology, Austria
– Stefan Pickl, University of the Bundeswehr Munich, Germany
We look forward to your submission and to welcoming you to Singapore in December.
Sincerely,
 August 25th, 2026  Daniela Lopez de Luise
Upcoming IAPR TC4/ IEEE Biometrics Council Webinar
Title: Identity Security in the Age of Deepfakes
Speaker: Prof. Siwei Lyu, University at Buffalo, USA
When: August 27, 2026 at 8:00 AM US Eastern Time (2:00 pm CEST, 8:00 PM Beijing Time)
Where: Online (Zoom)
Registration (free but required): https://us06web.zoom.us/webinar/register/WN_O4u0j2pRRbqueYItyIooJA
Abstract:
Rapid advances in generative AI have made it increasingly easy to synthesize or manipulate faces, voices, and real-time audiovisual streams, creating new challenges for biometric identity systems. This talk examines how deepfakes can affect different stages of the biometric pipeline, including synthetic identity creation, impersonation, morphing, and real-time digital injection. It will clarify the complementary roles of biometric matching, presentation attack detection and liveness, and media forensics, and review the forensic evidence that current deepfake detectors exploit.
The talk will also discuss why deepfake detection remains difficult in real-world settings and argue for moving beyond a single “real or fake” detector toward layered, evidence-based and risk-aware biometric authentication. The webinar should be relevant to researchers, practitioners, students, and security professionals working in biometrics, identity verification, media forensics, AI security, fraud prevention, and trustworthy AI.
About The Speaker:
Siwei Lyu is a SUNY Distinguished Professor at the University at Buffalo, State University of New York, where he directs the Institute for AI and Data Science and the UB Media Forensics Lab. His research focuses on digital media forensics, deepfake and AI-generated media detection, and trustworthy AI. He leads the development of DeepFake-o-Meter, an open platform integrating state-of-the-art deepfake detection methods for research and real-world analysis. He is a Fellow of IEEE and IAPR.
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Marija Ivanovska, PhD
Assistant | Laboratory for Machine Intelligence
Faculty of Electrical Engineering, University of Ljubljana
August 25th, 2026 Daniela Lopez de Luise
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CALL FOR PAPERS – IEEE Transactions on Services Computing (IEEE TSC)
Special Issue on Large Language Models in Service-Oriented Ecosystems Design: Advances and Applications
Special Issue Website: https://www.computer.org/digital-library/journals/tsc/cfp-language-models-ecosystems-design====================================================================During the latest years, Large Language Models (LLMs) have emerged as a transformative technology opening new frontiers and opportunities across many areas of ICT, including complex systems design and engineering. One of the most promising applications lies in service-oriented ecosystems, where LLMs can enhance design processes, support service identification, streamline service discovery, optimize composition mechanisms, and, more generally, enable intelligent automation within Service-Oriented Architectures (SOAs), thus representing a significant – yet still largely underexplored – opportunity for research and practice. In this context, combining LLMs with the modular and interoperable principles of SOAs could open new research directions for designing and developing adaptive, context-aware, and self-optimizing service ecosystems. This integration may enable systems to dynamically identify, discover, and compose services, reconfigure based on user needs, and continuously improve through natural language interactions. More broadly, the convergence of LLMs and SOAs denotes a potential paradigm shift in how distributed systems are conceptualized, designed, and implemented. It could lead to more flexible, responsive, and intelligent software architectures that are better aligned with evolving business goals and user requirements.
This Special Issue aims at bringing together cutting-edge research that explores the intersection of LLMs and service-oriented computing, showcasing both theoretical advancements and practical implementations that highlight how LLMs can improve efficiency, accuracy, and scalability in service-oriented solutions design.
In this respect, we welcome submissions that provide new insights into the application of LLMs in architectural decision-making, interoperability, and intelligent service identification, discovery and composition.
The call for this Special Issue is open to all researchers and practitioners, ensuring a broad and diverse range of contributions from academia and industry.
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TOPICS OF INTEREST
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We invite original research articles, review papers and case study papers on topics including, but not limited to:
• LLMs for Improving Efficiency, Accuracy, and Scalability of Service-Oriented Architectures
• LLM-Driven Approaches for Intelligent Service Identification, Discovery, Orchestration, and Composition
• LLM-Assisted Design of Service-Based Software Architectural Solutions
• LLM-Powered Service Interoperability and Integration Solutions
• Case Studies, Applications, and Real-World Implementations of LLMs in Service-Oriented Computing
• Assessing the Impact of LLMs on Reliability, Maintainability, and Performance in Service-Oriented Architectures
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SUBMISSION GUIDELINES
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Authors should submit original manuscripts not exceeding 14 pages following IEEE Transactions on Services Computing guidelines. All submissions must be made through the IEEE Author Portal.
Please select “Special Issue on Large Language Models in Service-Oriented Ecosystems Design: Advances and Applications” during submission.
Manuscripts must not be published or under review elsewhere.This Special Issue accepts extended versions of papers from conferences or workshops, under certain restrictions: the extended paper must present 30% additional core contributions (i.e. not limited to extending related works and background information sections) and must have a similarity score lower than 50% relative to the proceedings version. The proceedings paper must be provided at the time of submission and a description of the extension must be included in the cover letter.
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IMPORTANT DATES
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• Manuscript Submission Deadline: October 31, 2026
• First Round Notification: March 1, 2027
• Revised Manuscript Due: May 1, 2027
• Final Decision Notification: June 1, 2027
• Final Manuscript Submission Due: June 15, 2027
• Expected Publication: Mid 2027 (tentative)
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GUEST EDITORS
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• Prof. Boualem Benatallah, Dublin City University, Insight SFI Research Centre on Data Analytics, Ireland
• Dr. Massimiliano Garda, University of Brescia, Department of Information Engineering, Italy
• Dr. Ada Bagozi, University of Brescia, Department of Information Engineering, Italy
• PD Dr. Ilche Georgievski, University of Stuttgart, Department of Service Computing, Germany
• Distinguished Prof. Michael Sheng, School of Computing, Macquarie University, Australia
• Prof. Yingjie Wang, School of Computer and Control Engineering, Yantai University, China
Informativa sulla Privacy: https://www.unibs.it/it/node/1452
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