Track 1: Intelligent Data Science and Applications

Focus: Core data techniques integrated with domain applications across science, business, and engineering.

Topics

• Data Collection, Preprocessing & Mining
• Statistical Modeling and Inference
• Data Visualization & Summarization
• Bioinformatics and Biomedical Data Processing
• Geospatial and Sensor Data Analytics
• Image, Video, and Speech Processing
• Recommendation Systems and Social Media Analytics
• Business Models and Value Creation with Big Data
• Information Retrieval and Anomaly Detection
• Case Studies in Government, Healthcare, SMEs, and Public Sectors
• Blockchain and Secure Data Management
• Big Data in Biology, Physics, and Environmental Sciences
• MapReduce, Spark, and Distributed Data Frameworks

Track 2: Machine Learning and Cognitive Systems

Focus: From theory to real-world intelligent applications including robotics, industry, healthcare, and physical sciences.

Topics

• Supervised, Unsupervised & Reinforcement Learning
• Deep Learning & Large Language Models (LLMs)
• Natural Language Processing (NLP)
• Brain-Inspired Computation and Informatics
• Performance Modeling and Evaluation
• Intelligent Transportation and Navigation Systems
• Genetic Algorithms and Swarm Optimization
• Machine Learning in Civil, Mechanical, and Petroleum Engineering
• ML for Smart Diagnostics in Medicine and Energy Systems
• Human-in-the-loop AI and Decision Support
• Simulation of Physical Phenomena using ML

Track 3: Internet of Things and Smart Infrastructure

Focus: IoT technologies across domains including agriculture, smart cities, industrial automation, and energy systems.

Topics

• IoT Architectures, Middleware, and Protocols
• Smart City, Smart Village, and Smart Grid Applications
• IoT for Civil Engineering: Smart Structures, Monitoring
• IoT for Mechanical and Petroleum Systems: Predictive Maintenance
• Sensor Networks & Embedded Systems
• Location & Context Awareness
• Transportation and Traffic Management
• Remote Monitoring in Biomedical and Environmental Domains
• Energy Efficiency in IoT Deployments
• Secure IoT and Cyber-Physical Systems
• Machine-to-Machine Communication and Edge Intelligence

Track 4: Sustainable and Green Computing Systems

Focus: Energy-aware systems, sustainable computing, and computational models in material and environmental sciences.

Topics

• Green Computing and Energy-efficient Architectures
• Cloud and Grid Computing for Environmental Monitoring
• High-Performance and Parallel Computing
• Cyberinfrastructure Design and Deployment
• Material Informatics: AI for New Material Discovery
• Sustainable Computing in Civil and Mechanical Systems
• Environmental Data Analytics and Earth Observation
• Crowd Sourcing for Environmental and Social Applications
• Data-driven Models for Smart Agriculture and Water Systems
• Computation in Climate Science and Renewable Energy

Track 5: Computational Engineering and Scientific Modeling

Focus: Integration of computational intelligence with physics, biology, electrical, civil, and mechanical engineering.

Topics

• Computational Modeling in Fluid Dynamics, Structures, and Materials
• Digital Twin Systems in Engineering
• Data-driven Design Optimization in Civil and Mechanical Fields
• ML for Predictive Modeling in Petroleum and Energy Systems
• Intelligent Control Systems and Robotics
• AI and ML Applications in Electrical and Electronics Engineering
• Physics-Informed Machine Learning
• Simulation Tools for Complex Engineering Systems
• Biomedical Modeling and Simulation
• Cross-disciplinary Applications: Bio-Mechanical Systems, Neuroinformatics
• AI-Driven Fault Detection and Safety Modeling