EAIT 2026 | Emerging AI Technologies

Call for Papers (CFP Flyer)

The International Conference on Emerging AI Technologies centers on the theme "AI for Humanity." We believe the true measure of technological progress is its capacity to solve fundamental engineering challenges and enhance the human condition. Much like the industrial revolutions of the past, AI serves as a powerful catalyst for productivity and the evolution of the global workforce. This forum moves beyond narratives of replacement to focus on the reality of human augmentation, i.e., viewing AI not as a competitor to human labor, but as a transformative tool designed to automate routine tasks, optimize complex systems, and empower the individual. Our objective is to showcase how emerging AI architectures, from autonomous agents to physics-informed models, can be harnessed to address the most significant hurdles of our time, including infrastructure resilience, energy security, and the precision of personalized healthcare. This conference provides a premier global forum for researchers, engineers, and industry pioneers to share breakthroughs in AI architectures and their cross-sector applications. We seek to explore the frontier where cutting-edge hardware, such as Edge AI and neuromorphic chips, meets the transformative power of generative media and multi-agent swarms. Join us as we illuminate the next era of AI-native innovation and chart the course for responsible, high-impact technological advancement.

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.