Foundation Models, LLMs & Multimodal AI

• Large Language Models (LLMs) and foundation model architectures
• Multimodal AI: vision language, audio language, video language systems
• Retrieval Augmented Generation (RAG) and knowledge grounded AI
• Agentic AI, tool using agents, and autonomous LLM systems
• Safety, alignment, hallucination mitigation, and trustworthy LLMs
Generative AI & Creative Intelligence

• Diffusion models and generative transformers
• Text, image, audio, and video generation
• Generative 3D models (NeRFs, Gaussian splatting, 3D diffusion)
• Synthetic data generation and evaluation
• Generative agents, simulation environments, and digital twins
Robotics, Embodied AI & Autonomous Systems

• Embodied AI and sensorimotor learning
• Foundation models for robotics
• Human robot interaction and collaboration
• Autonomous navigation, manipulation, and control
• Sim to real transfer and robot learning
AI for Science, Medicine & Engineering

• AI for drug discovery, genomics, and computational biology
• Scientific machine learning and physics informed AI
• AI for climate modeling, sustainability, and energy systems
• Medical imaging, diagnostics, and clinical decision support
• AI for materials science and chemistry
Machine Learning Theory & Algorithms

• Optimization, search, and learning theory
• Self supervised, weakly supervised, and unsupervised learning
• Reinforcement learning and RLHF
• Probabilistic modeling and Bayesian learning
• Causal inference, causal discovery, and causal representation learning
Knowledge, Reasoning & Cognitive Systems

• Knowledge graphs and neuro symbolic AI
• Automated planning and decision making
• Explainable and interpretable AI
• Cognitive architectures and computational reasoning
• Semantic web technologies and linked data
Computer Vision, Speech & Language Technologies

• Vision transformers and next generation CV models
• 3D vision, scene understanding, and embodied perception
• Speech recognition, synthesis, and conversational AI
• Advanced NLP, multilingual models, and low resource learning
• Document intelligence and information extraction
AI Safety, Ethics, Fairness & Governance

• Robustness, adversarial ML, and red teaming
• Fairness, bias mitigation, and responsible AI
• AI governance, regulation, and policy frameworks
• Societal impacts of AI deployment
• Ethical considerations in generative and autonomous systems
Scalable, Efficient & Green AI Systems

• Distributed training, large scale ML systems, and HPC
• Model compression, pruning, quantization, and distillation
• Energy efficient AI and carbon aware computing
• MLOps, deployment pipelines, and inference optimization
• AI hardware acceleration (GPUs, TPUs, NPUs, custom chips)
Edge AI, IoT Intelligence & Pervasive Computing

• TinyML and on device learning
• Edge cloud collaborative intelligence
• Ambient intelligence and smart environments
• Real time AI for IoT and cyber physical systems
Data, Evaluation & Benchmarking

• Dataset creation, curation, and governance
• AI evaluation frameworks and benchmark design
• Safety and robustness testing
• Data centric AI and automated data quality improvement
Applied AI & Industry Innovation

• AI for finance, manufacturing, and supply chains
• Smart cities, transportation, and autonomous mobility
• AI for cybersecurity and threat detection
• AI in education, personalized learning, and EdTech
• Industrial automation and intelligent systems

Hard copy of the proceedings will be distributed during the Conference. The softcopy will be available on AIRCC digital library.