AIAD 2026
5th International Conference on Artificial Intelligence Advances (AIAD 2026)
July 29 ~ 30, 2026, Virtual Conference
Scope & Topics
5th International Conference on Artificial Intelligence Advances (AIAD 2026)
serves as a premier global forum for presenting cutting edge research, breakthrough innovations and emerging trends in advanced Artificial Intelligence. As AI continues to transform science, industry and society at an unprecedented pace, AIAD 2026 brings together leading researchers, practitioners and industry experts to exchange ideas, explore new methodologies and discuss the challenges and opportunities shaping the future of intelligent systems.
Call for Papers
AIAD 2026
covers the full spectrum of modern AI, from foundational machine learning theory and large scale deep learning models to autonomous agents, robotics, AI for science and multidisciplinary applications. The conference emphasizes both core AI research and advanced cross disciplinary domains, reflecting the rapidly expanding influence of AI across computer science, engineering, healthcare, finance, education, sustainability and beyond.
Authors are invited to contribute original research articles, innovative project results, comprehensive surveys and industrial case studies that demonstrate significant advances in Artificial Intelligence, Computer Science and Information Technology.
Topics of interest include, but are not limited to, the following:
-
Foundations of Artificial Intelligence
- Machine Learning Theory and Optimization
- Probabilistic Modeling and Bayesian Inference
- Causality and Causal Reasoning
- Knowledge Representation and Reasoning
- Neuro Symbolic AI
- Logic Based and Model Based Reasoning
-
Deep Learning and Representation Learning
- Deep Neural Architectures
- Self Supervised and Unsupervised Learning
- Continual, Lifelong and Transfer Learning
- Multimodal Representation Learning
- Efficient AI (Pruning, Quantization, Distillation)
- Distributed and Large Scale Training
-
Large Language Models (LLMs) and Foundation Models
- Pretraining, Scaling Laws and Architecture Design
- Retrieval Augmented Generation (RAG)
- LLM Agents and Tool Using Models
- Hallucination Mitigation and Reliability
- Alignment, RLHF and Human Feedback Integration
- Domain Specific Foundation Models
-
Agentic AI and Autonomous AI Agents
- Autonomous LLM Agents
- Multi Step Planning and Tool Use
- Agent Evaluation and Benchmarking
- Multi Agent Collaboration and Competition
- Embodied Agents and Interactive Environments
-
Generative AI and Creative Intelligence
- Diffusion Models, GANs and VAEs
- Text to Image, Text to Video and Multimodal Generation
- Synthetic Data Generation
- Human AI Co Creativity
- Evaluation, Safety and Governance of Generative Models
-
Reinforcement Learning and Decision Making
- Deep RL
- Multi Agent RL
- Offline RL and Imitation Learning
- RLHF (Reinforcement Learning from Human Feedback)
- Planning, Control and Sequential Decision Making
-
Explainable, Trustworthy and Responsible AI
- Explainable AI (XAI)
- AI Ethics, Fairness and Bias Mitigation
- AI Safety, Alignment and Red Teaming
- Robustness, Reliability and Adversarial ML
- Privacy Preserving AI (Federated Learning, Differential Privacy)
- Governance, Policy and Societal Impacts
-
Computer Vision and Multimodal Perception
- Image and Video Understanding
- 3D Vision, SLAM and Scene Reconstruction
- Vision Language Models
- Medical and Scientific Imaging
- Visual Reasoning and Explainability
-
Natural Language Processing and Speech Technologies
- Language Modeling and Text Understanding
- Conversational AI and Dialogue Systems
- Machine Translation
- Information Retrieval and Question Answering
- Speech Recognition and Speech Synthesis
- NLP for Low Resource Languages
-
Robotics, Embodied AI and Autonomous Systems
- Robot Learning and Sim to Real Transfer
- Embodied LLMs and Vision Language Action Models
- Autonomous Vehicles and Navigation
- Swarm Robotics and Collective Intelligence
- Human Robot Interaction
-
AI for Code, Software Engineering and Program Synthesis
- Code Generation and Completion
- Automated Debugging and Program Repair
- AI Assisted Software Engineering
- Program Synthesis and Verification
- Software Agents and Developer Tools
-
AI for Networks, Communications and IoT
- AI for 5G/6G Networks
- Edge AI and TinyML
- AI Enabled IoT Systems
- Network Optimization and Traffic Prediction
- Cognitive Cyber Physical Systems
-
Quantum AI and Emerging Computing Paradigms
- Quantum Machine Learning
- Quantum Optimization
- Hybrid Quantum Classical AI Systems
- Neuromorphic Computing
-
Data Centric AI, Synthetic Data and Knowledge Discovery
- Data Quality, Governance and Curation
- Synthetic Data Pipelines
- Graph Learning and Network Science
- Knowledge Graphs and Semantic Reasoning
- Neural Search, Retrieval and Ranking
- Recommender Systems
-
AI Systems, Infrastructure and MLSys
- GPU/TPU Optimization
- Compilers for AI and ML Frameworks
- Distributed Inference and Serving
- Memory Efficient Training
- Systems for LLMs and Foundation Models
-
AI Benchmarking, Evaluation and Standards
- Benchmark Design and Evaluation Protocols
- LLM and Agent Evaluation
- Safety and Robustness Benchmarks
- Standardization and Reproducibility
-
AI for Science, Engineering and Simulation
- AI for Physics, Chemistry and Materials
- AI Accelerated Scientific Simulation
- Digital Twins and Synthetic Environments
- AI for Engineering Design and Optimization
Bio AI, Health AI and Computational Life Sciences
- AI in Healthcare and Clinical Decision Support
- Bioinformatics and Computational Biology
- Drug Discovery and Molecular Modeling
- Medical Imaging and Diagnostics
- AI for Public Health and Epidemiology
-
AI for Society, Sustainability and Global Challenges
- AI for Climate Change and Environmental Monitoring
- AI for Energy Systems and Smart Grids
- AI for Agriculture and Food Security
- AI for Disaster Prediction and Response
- AI for Education and Learning Analytics
- Computational Social Science and Policy Modeling
-
Security, Privacy and Cyber Defense
- AI in Cybersecurity
- Secure Model Training and Deployment
- Privacy Preserving ML
- Threat Detection and Anomaly Analysis
-
Human Centered AI and Intelligent Interaction
- Human AI Collaboration
- Intelligent User Interfaces
- Human Computer Interaction (HCI)
- Affective Computing and Emotion Aware AI
- Usability, Trust and User Experience
-
Industrial AI, MLOps and Applied AI Systems
- AI in Finance, FinTech and Business Analytics
- AI in Legal Tech and Compliance
- Industrial Automation and Smart Manufacturing
- MLOps, Deployment and AI Infrastructure
- Real World AI Applications and Case Studies
Paper Submission
Authors are invited to submit papers through the conference
Submission System
by May 30, 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
International Journal on Cybernetics & Informatics (IJCI)
(Confirmed).
Selected papers from AIAD 2026, after further revisions,
will be published in the special issue of the following journals.
Important Dates
| Submission Deadline |
: |
May 30, 2026 |
| Authors Notification |
: |
June 20, 2026 |
| Registration & camera - Ready Paper Due |
: |
June 27, 2026 |
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Contact Us
Here’s where you can reach us :
aiad@aiad2026.org
or
aiadconference@yahoo.com
User Name :
laksh21
Posted 28-05-2026 on 19:47:30
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