Artificial intelligence is a broad area of research. We encourage researchers to submit papers in the following areas but not limited to:
Scope and Topics

Machine Learning & Deep Learning
Neural networks and representation learning
Reinforcement learning and decision-making
Explainable AI and trustworthy ML
Natural Language Processing & Speech Recognition
Large language models and generative AI
Multimodal AI and human-AI interaction
Sentiment analysis and discourse modeling
Computer Vision & Image Processing
Object detection and scene understanding
Medical imaging and biometrics
AI-driven creative applications (e.g., art, design, and multimedia)
Robotics & Autonomous Systems
AI for robotics and intelligent automation
Multi-agent systems and swarm intelligence
Human-robot interaction



AI for Society, Ethics & Applications
AI for healthcare, finance, and smart cities
Ethical AI, bias mitigation, and fairness
AI-driven education and learning analytics
AI Theory & Algorithms
Computational intelligence and optimization
Knowledge representation and reasoning
Probabilistic modeling and uncertainty in AI
Agentic AI
Defining agency in AI
Reinforcement learning in agentic AI systems
Multi-agent coordination and negotiation strategies
Handling uncertainty and risk in agentic AI decision-making
Large Language Model
Interpretability and Explainability
Alignment and Safety
Multilingual & Cross-Lingual Learning
Agentic AI with LLM


Call for Special Sessions
Special Session 1

The Secure Edge-AI (SEAI) special session aims to explore the intersection of artificial intelligence (AI) and edge computing with a focus on security, privacy, and resilience. As AI-powered edge devices proliferate across industries such as healthcare, autonomous systems, IoT, and smart cities, ensuring their security and robustness is crucial.

We welcome submissions on topics including, but not limited to:

Secure AI models and architectures for edge computing
Privacy-preserving AI techniques
Adversarial attacks and defenses in Edge-AI
Lightweight cryptographic techniques for AI at the edge
Trust and authentication mechanisms in Edge-AI deployments
Secure data transmission and storage for edge intelligence
AI-driven intrusion detection for edge networks
Blockchain and decentralized security for Edge-AI
Hardware security for AI-enabled edge devices

Special Session 2

The AI in Industry (AIIN) special session aims to explore the use of AI and digital transformation (DX) in industry. Applications such as AI-powered systems for quality control, safety and security monitoring systems in manufacturing, smart manufacturing, fintech and economics applications are essential.

We welcome submissions on topics including, but not limited to:

Machine vision
Optics Technologies for Vision System
Defect Inspection System
Visual Inspection
Document Analysis and Understanding
Human Action Recognition and Understanding
Voice Processing
Vision Language Models
Evolution of cognition
Evolutionary game theory
Behavioural economics and psychology

Tutorial 1

This tutorial introduces the audience to the application of Generative AI (GenAI) for processing multimedia documents in small and medium-sized healthcare facilities. The presenters, including healthcare providers and GenAI researchers, will demonstrate how GenAI can manage information efficiently.

In developing countries like India, many clinics face challenges due to limited IT infrastructure, relying on handwritten or printed prescriptions and discharge sheets. The absence of structured databases complicates healthcare management. Additionally, radiologists and diagnostic professionals often dictate their findings, which are transcribed by secretaries. Training and maintaining qualified staff is another challenge for these clinics.

Generative AI offers a promising solution by digitizing handwritten, printed, and voice data from physicians, which can then be stored in a structured data warehouse. Our initiative involves collecting over a hundred voice and paper documents to build a comprehensive database that can be queried using natural language. This approach aims to streamline data management in clinics, enhancing the overall efficiency and accuracy of healthcare delivery.

The tutorial will depict various scenarios in SME healthcare facilities and present corresponding multimedia documents. We will demonstrate how different GenAI technologies can effectively process these documents. While the solutions described will increase the efficiency of information processing in healthcare facilities, there are challenges that make full automation difficult. We will identify these challenges in the multimedia documents, opening up new directions for further research.

Tutorial 2

This tutorial provides a hands-on introduction to text analytics using Python, focusing on NLP fundamentals, practical use of libraries like NLTK and spaCy, and sentiment analysis techniques. Designed for researchers, postgraduate students, and NLP beginners, the session equips participants with essential skills in processing unstructured textual data. Key topics include tokenization, stemming, lemmatization, POS tagging, and real-world sentiment analysis applications.