12th International Conference on Artificial Intelligence and Applications (AIFU 2026)
June 27 ~ 28, 2026, Copenhagen, Denmark
Scope & Topics 12th International Conference on Artificial Intelligence and Applications (AIFU 2026) is a forum for presenting new advances and research results in the fields of Artificial Intelligence. The conference will bring together leading researchers, engineers and scientists in the domain of interest from around the world. The scope of the conference covers all theoretical and practical aspects of the Artificial Intelligence.
The scope of AIFU 2026 spans both the theoretical foundations and practical applications of AI, reflecting the rapid evolution of the field from machine learning, deep learning, and intelligent reasoning to foundation models, generative AI, robotics, and AI driven scientific discovery. The conference welcomes contributions that advance our understanding of modern AI techniques, architectures, algorithms, and real world deployments, as well as interdisciplinary work that bridges AI with domains such as healthcare, climate science, engineering, and human computer interaction.
Authors are invited to submit high quality research articles, case studies, survey papers, and industrial experiences that demonstrate significant progress in Artificial Intelligence and its diverse applications. Submissions may highlight novel algorithms, innovative systems, experimental results, or applied solutions that address real world challenges.
Topics of interest include, but are not limited to, the following
Foundation Models, Generative AI and Large Scale Learning
- Large Language Models (LLMs), Vision Language Models (VLMs) and Multimodal Foundation Models
- Generative AI: Diffusion Models, GANs, Autoregressive Models and Creative AI
- Retrieval Augmented Generation (RAG), Memory Augmented Models and Long Context AI
- Scaling Laws, Foundation Model Engineering and Model as a Service Architectures
- Efficient AI: Distillation, Quantization, Pruning and Low Compute Training
- Continual Learning, Lifelong Learning and Transfer Learning
- Synthetic Data Ecosystems: Generation, Alignment, Governance and Evaluation
Machine Learning, Deep Learning and Computational Intelligence
- Supervised, Unsupervised, Self Supervised and Contrastive Learning
- Reinforcement Learning, Multi Agent RL and Decision Making Systems
- Graph Neural Networks, Relational Learning and Structured Prediction
- Probabilistic Modeling, Bayesian Learning and Uncertainty Estimation
- Neuro Symbolic AI, Hybrid Reasoning and Differentiable Programming
- Explainable AI (XAI), Interpretability, Trustworthy ML and Model Transparency
Knowledge Representation, Reasoning and Cognitive AI
- Knowledge Graphs, Ontologies and Semantic Reasoning
- Automated Planning, Heuristics and Intelligent Decision Making
- Causal AI: Causal Discovery, Causal Representation Learning and Counterfactual Reasoning
- Cognitive Architectures, Human AI Interaction and Cognitive Modeling
- Neuroscience Inspired AI, Biologically Plausible Learning and Neural Coding
- Logic Based AI, Constraint Solving and Automated Theorem Proving
Natural Language Processing, Conversational AI and Agentic Systems
- Text Understanding, Summarization, Question Answering and Information Extraction
- Dialogue Systems, Conversational Agents and LLM Based Assistants
- Agentic AI: Tool Using Agents, Autonomous Research Agents and Multi Agent Collaboration
- Multi Step Planning, Reasoning Chains and Agentic Workflows
- Multilingual NLP, Low Resource NLP and Cross Lingual Transfer
- Speech Recognition, Speech Synthesis and Spoken Language Understanding
Computer Vision, Robotics and Embodied Intelligence
- Image/Video Understanding, Object Detection and Scene Analysis
- Vision Language Models, Visual Reasoning and Multimodal Perception
- Robotics, Motion Planning and Autonomous Systems
- Embodied AI: Vision Language Action Models, Instruction Following Agents and Manipulation
- Simulation to Real Transfer, 3D Perception and Embodied Reinforcement Learning
- Human Robot Interaction and Collaborative Robotics
AI for Science, Engineering and Real World Applications
- AI for Chemistry, Biology, Physics and Materials Science
- AI for Drug Discovery, Protein Design and Molecular Simulation
- AI for Climate Modeling, Sustainability and Environmental Intelligence
- AI for Finance, Law, Education, Manufacturing and Smart Cities
- AI Driven Software Engineering, Automated Code Generation and Program Synthesis
- Intelligent Transportation, Autonomous Vehicles and Mobility Systems
Responsible AI, Ethics, Fairness and Safety
- Bias Detection, Fairness and Inclusive AI
- Privacy Preserving AI, Federated Learning and Secure ML
- AI Safety, Alignment, Red Teaming and Jailbreak Prevention
- Robustness to Adversarial Attacks and Distribution Shift
- Governance, Policy, Regulation and Societal Impact of AI
- AI Risk Management, Certification and Compliance
Fuzzy Systems, Soft Computing and Hybrid Intelligence
- Fuzzy Logic, Type 2 Fuzzy Systems and Approximate Reasoning
- Neuro Fuzzy Systems, Evolutionary Fuzzy Systems and Hybrid Soft Computing
- Fuzzy Modeling, Control Systems and Intelligent Automation
- Soft Computing for Optimization, Pattern Recognition and Decision Support
Data Mining, Knowledge Discovery and Intelligent Information Systems
- Data Mining, Predictive Analytics and Pattern Recognition
- Information Retrieval, Semantic Search and Vector Databases
- Big Data Analytics, Stream Processing and Real Time Intelligence
- Cognitive Informatics and Intelligent Information Systems
AI Engineering, Infrastructure and Scalable Architectures
- AI Evaluation Science: Benchmarking, Meta Evaluation and Stress Testing
- AI Observability, Monitoring, Debugging and Failure Analysis
- MLOps, Model Deployment, Lifecycle Management and AI Pipelines
- Distributed AI, Parallel Training and High Performance ML Systems
- AI Hardware Acceleration (GPUs, TPUs, Neuromorphic Computing)
- Software and Hardware Architectures for Scalable AI Systems
Social AI, Computational Social Science and Human Centered AI
- AI for Social Networks, Influence Modeling and Social Simulation
- Toxicity Detection, Content Moderation and Misinformation Analysis
- AI for Political Discourse, Public Opinion and Social Dynamics
- Human Centered AI, User Modeling and Personalized AI Systems
Paper Submission Authors are invited to submit papers through the conference Submission System by April 11, 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 Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) (Confirmed). Selected papers from AIFU 2026, after further revisions, will be published in the special issue of the following journals. Important Dates | Submission Deadline | : | April 11, 2026 | | Authors Notification | : | May 23, 2026 | | Final Manuscript Due | : | May 30, 2026 |
Co - Located Event ***** The invited talk proposals can be submitted to aifu@aifu2026.org
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