13th International Conference on Data Mining and Database (DMDB 2026)
March 14~ 15, 2026, Vienna, Austria Scope & Topics 13th International Conference on Artificial Intelligence and Applications (AIAP 2026)
Artificial Intelligence continues to redefine the boundaries of science, engineering, and society. As AI systems grow more capable, multimodal, autonomous, and integrated into real world environments, the need for rigorous research, responsible innovation, and cross disciplinary collaboration has never been greater.
AIAP 2026 provides a premier international forum for researchers, practitioners, and industry leaders to share breakthroughs, explore emerging directions, and discuss the challenges shaping the future of AI. We invite high quality submissions presenting original research, significant results, innovative applications, and comprehensive surveys across the full spectrum of Artificial Intelligence.
AIAP 2026 invites submissions in all areas of Artificial Intelligence, including but not limited to the following major themes: Topics of interest include, but are not limited to, the following 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
Paper Submission Authors are invited to submit papers through the conference Submission System by January 10, 2026. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from AIAP 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | January 10, 2026 | | Authors Notification | : | January 24, 2026 | | Final Manuscript Due | : | January 31, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to aiap@ccseit2026.org
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