Track 4 : Artificial Intelligence in Real-world Applications and Automation

• Deep Learning Architectures for Real-Time Decision Making
• Transformer Models and Applications in NLP
• Computer Vision for Image, Video, and Object Recognition
• AI in Autonomous Vehicles and Intelligent Transportation Systems
• Explainable AI (XAI) and Interpretability in AI Systems
• Multi-agent Systems and Swarm Intelligence
• Reinforcement Learning in Robotics and Game Environments
• AI for Edge and Embedded Devices
• Federated Learning and Privacy-Preserving AI

Track 5 : Data Science and Predictive Analytics for Intelligent Insights

• Data handling, analysis, and prediction techniques using modern data science methodologies
• Data Mining Techniques for Knowledge Discovery
• Scalable Machine Learning with Big Data Technologies
• Time Series Analysis and Forecasting Models
• Advanced Statistical Modelling and Inference
• Data Cleaning, Preprocessing, and Feature Engineering
• Predictive Analytics in Finance, Retail, and Healthcare
• Cloud-based Data Pipelines and Infrastructure
• Interactive Dashboards and Data Storytelling Techniques
• Bias, Fairness, and Ethics in Data Science
• Real-time Analytics and Streaming Data Applications

Track 7 : AI-Driven Intrusion Detection for Large-Scale Networks

• Hybrid ML Model for Malware Detection
• Federated Learning Framework for IoT Intrusion Detection
• Adaptive AI Cybersecurity for Industry 4.0
• Quantum-Resistant ECC for Secure Communication
• IoMT Cybersecurity Framework for Intrusion Detection

Track 9 : Emerging Trends in Distributed and Cloud Technologies

• Cloud Infrastructure and Architectures
• Applications and Integration
• Security, Privacy, and Reliability
• Emerging and Sustainable Technologies