5th International Conference on Artificial Intelligence Advances (AIAD 2026)

Program Committee

Accepted Papers

Virtual Conference

Scope
5^th 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 Modelingand 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 Modelingand Text Understanding
Conversational AI and Dialogue Systems
Machine Translation
Information Retrieval and Question
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 andIoT

AI for 5G/6G Networks
Edge AI andTinyML
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 andMLSys

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, MLOpsand Applied AI Systems

AI in Finance, FinTechand 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 16, 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 journal.

Important Dates

Submission Deadline

May 16, 2026

Authors Notification

June 20, 2026

Registration & camera - Ready Paper Due

June 27, 2026

Proceedings

The soft copy of the proceedings will be available on Journal web pages.

The Registration fee is 250 USD for accepted article Authors. Atleast one author of accepted paper is required to register at the full registration rate.