Architectures, algorithms, and engineering of modern computing infrastructures. Topics include edge/fog continuum, cloud-native systems (containers, Kubernetes, serverless), distributed systems, scalable storage/compute, HPC/parallel computing, networked systems, cyber-physical systems, digital twins (systems aspects), blockchain/DLT as infrastructure, observability, reliability, and green/sustainable computing at system level.
Protection, assurance, and compliance across systems and AI-enabled services. Topics include secure architectures, zero trust, authentication/authorization, secure protocols, vulnerability analysis, intrusion detection, malware, secure software/hardware, formal methods for security, post-quantum readiness, privacy-enhancing technologies (DP, MPC, HE), secure federated learning (security/privacy aspects), auditability, governance, risk, and safety/security evaluation.
End-to-end data lifecycle and knowledge-centric systems. Topics include databases (relational/NoSQL/NewSQL), lakehouse/data fabrics, data integration, data quality, provenance/lineage, stream processing, semantic data management, knowledge graphs/ontologies, information retrieval and search (including vector databases as retrieval infrastructure), data spaces/interoperability, metadata management, and data-centric benchmarking.
Core AI/ML methods beyond modality-specific NLP/CV. Topics include learning theory, deep learning, graph learning, causal ML, reinforcement learning, neuro-symbolic and logic-based AI, planning, multi-agent systems, trustworthy/responsible AI (fairness, robustness, interpretability as AI methodology), AutoML, MLOps/LLMOps methodology, and compute-efficient AI (distillation, compression).
Human-language technologies and language-centric foundation models. Topics include NLP, speech processing, multilinguality, low-resource NLP, information extraction, summarization, machine translation, dialogue systems, LLMs (prompting, fine-tuning, alignment, evaluation), agentic conversational systems, Retrieval-Augmented Generation (RAG) as a language-system design pattern, and human-centered language applications (education, healthcare, smart services).
Visual/audio signal understanding and generation, and multimodal fusion. Topics include computer vision, video analytics, 3D vision, remote sensing vision, medical imaging, AR/VR/XR, multimedia retrieval for visual/audio content, multimodal learning (vision–language–audio), generative media (diffusion, video generation), robustness, generalization, and evaluation for perception systems, and edge vision deployment (application side).
Manuscripts must be prepared in IEEE 8.5" x 11" two-column conference format (10pt font). Maximum 8 pages. Double-blind review. All accepted papers will appear in IEEE Xplore and be indexed by Scopus and Web of Science.
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