Program Overview

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P.s. The program is only for reference, and the final program will be available on Middle August, 2026.

Publication and Indexing

1) All the accepted and presented papers will be submitted for inclusion into conference proceeding subject to meeting the publisher’s scope and quality requirements. The publisher will submit articles to Engineering Village, Scopus, Web of Science and other databases for review and indexing after publication.

2) Selected papers with great extension will be recommended to publish in special issue of international journals:
Choice 1: Wireless Networks (Springer, SCIE, IF 2.1)
Collection: AI-powered Secure and Smart Wireless Networks
https://link.springer.com/collections/cifddiacgg
Due Date: 12/31/2026

Choice 2: Applied Sciences (MDPI, SCIE, IF 2.2)
Special Issue: Artificial Intelligence: Fundamental Research and Emerging Applications in the Era of Autonomous Systems
https://www.mdpi.com/journal/applsci/special_issues/3WE2F8CI6C
Due Date: 05/20/2027

Choice 3: Sensors (MDPI, SCIE, IF 3.5)
Special Issue: AI-Driven Intelligent Communication
https://www.mdpi.com/journal/sensors/special_issues/WPHC1C9155
Due Date: 10/24/2026 (likely will be extended)

Call for Papers-topics (CFP Flyer)

Track 1: Generative Models and Synthetic Media
• Multimodal Synthesis: Latent diffusion models, transformer-based video generation, and cross-modal alignment.
• Neural Rendering: Neural Radiance Fields, 3D Gaussian Splatting, and high-fidelity 3D reconstruction.
• Computational Creativity: Algorithmic music composition, generative design, and the ethics of synthetic content.
• Digital Authenticity: Forensics for deepfake detection and cryptographic watermarking of AI outputs.

Track 2: Agentic Systems and Decentralized Intelligence
• Autonomous Agents: Task-oriented reasoning, tool-use in Large Language Models (LLMs), and self-evolving code agents.
• Swarm & Multi-Agent Intelligence: Collaborative decision-making, decentralized optimization, and agent-based social simulation.
• Adaptive Environments: Procedural content generation and behavioral modeling for non-player characters in immersive worlds.
• Human-Agent Interaction: Collaborative decision-making, trust-based delegation, and symbiotic workflows for human-AI augmentation.

Track 3: Efficiency, Edge, and Privacy-Preserving AI
• EdgeAI: TinyML architectures, model quantization, and knowledge distillation for resource-constrained devices.
• Hardware-Software Co-Design: Neuromorphic computing, low-power AI accelerators, and on-chip learning.
• Distributed Privacy: Federated learning, differential privacy, and secure multi-party computation.

Track 4: AI for Science and Engineering
• Infrastructure Resilience: AI-driven structural health monitoring and predictive maintenance for bridges, power grids, and transit systems.
• Energy Optimization: Intelligent control of smart grids, fusion energy modeling, and battery chemistry discovery.
• Physics-Informed Neural Networks: Integrating conservation laws into AI models for fluid dynamics and solid mechanics.
• Materials Informatics: Accelerating the discovery of high-performance alloys and semiconductors using generative models.

Track 5: Socio-Technical Applications and EdTech
• Precision Healthcare: AI-driven diagnostic assistance in radiology and pathology; wearable-based longitudinal health monitoring.
• Algorithmic Finance: Real-time fraud detection, automated risk assessment, and high-frequency predictive analytics.
• Next-Generation Pedagogy: Adaptive learning systems, automated feedback loops, and AI-assisted curriculum design.
• Universal Accessibility: AI-driven sensory substitution, real-time translation, and assistive mobility technologies.

Track 6: AI for Human Empowerment and Society
• Augmented Productivity: AI-human collaborative workflows and the transformation of the digital workplace.
• AI for Social Good: Mitigating global inequality, disaster response optimization, and food security.
• Ethics of Augmentation: Designing transparent and unbiased systems that prioritize human autonomy.
• Future of Labor: Economic modeling of AI-driven productivity gains and new job category creation.
• Public Trust and Literacy: Strategies for AI explainability and democratic access to foundation models.