IACIDS’23 aims to bring forth together leading industry experts, academic professionals, researcher personnel and scholars to exchange as well as share their knowledge, ideas, experiences and also interesting and notable research outcomes in every aspect of Data Science along with Emerging Technologies. This theme highlights revolutionizing the future through innovative ideas and findings in the fields of AI, Communication, IoT, Data Engineering, and Security that have the potential to improve our daily lives significantly. From AI-powered virtual assistants to 5G technology and from smart homes to secure blockchain transactions, these advancements pave the way for a more efficient, convenient, and secure future. This theme underscores the importance of continued research and development in these fields to ensure that the benefits of these technologies are fully realized, and the quality of life for all is enhanced. The readers of this book would be able to process and analyze vast amounts of data quickly, dramatically improve the efficiencies of their workplaces and can, augment the work humans can do, create new jobs based on the latest communication technologies, help businesses track, monitor, uncover and analyze customer data faster than before, predict shifts or trends in customer behaviour before they happen in a business, help businesses to make better decisions, to save time and money, and to understand their customers better, gain knowledge of preventing loss of sensitive or critical information that directly affect your competitiveness and cash flow, also damage your reputation.

 Conference Tracks

The conference has multiple tracks covering areas of AI , Communication IoT, data Engineering and security.

• Artificial intelligence concepts & algorithms
• Explainable & Trustworthy AI
• Computational intelligence
• Artificial intelligence in healthcare
• Artificial Intelligence in Recommender Systems
• Blockchain
• Identity Management and Object Recognition
• Graphs & Networks
• Digital transformation and innovation
• Tools and Methodologies for design thinking
• Industry 4.0
• Intelligent and Smart Grid System
• Green Computing
• Robotics and Process Automation (RPA)

• Data Mining and Knowledge Discovery
• Data Visualization and Interactive Data Exploration
• Artificial Intelligence and Data Analysis
• Data Models, Semantics, Query Languages
• Multimodal Data Analysis
• Stream Data Processing
• Big Data Systems Modelling, Analysis, and Simulation
• Applied cryptography in data security           
• Network security        
• Big data security        
• Secure cloud computing        
• Data protection          
• Mining text and semi-structured data
• Multimedia mining (audio/video)
• Wireless and mobile security
• Temporal and spatial data mining

Track 3: Communication and IoT Intelligence

• WirelessNetworks
• Mobile Cloud Computing (MCC) and IoT
• Next Generation Networks
• Fog/Cloud-Based IoT Architectures
• Machine-To-Machine, Device-To-Device, Vehicle-To-Vehicle Communications
• AI/ML for Smart/Intelligent Communication Networks
• Signal Processing and Imaging Systems
• GIS and Remote Sensing

Track 4: Emerging Technologies

• AI for Green communication systems and network
• Knowledge Engineering
• Quantum AI & quantum machine learning
• Social Media Analytics
• Cyberspace Operations
• Bioinspired Computing
• VR and AR in various industries, such as gaming, healthcare, education, and marketing
• 5G and edge computing for faster and more efficient data processing
• Autonomous vehicles and drones for transportation and logistics
• Robotics and automation for increased efficiency and productivity in manufacturing and services
• Biotechnology and genetic engineering for personalized medicine and improved agriculture
• Renewable energy and energy storage for a sustainable future
• Cloud computing and SaaS for business agility and innovation.
• Web mining

Track 5: Economics and Data Analytics

• Regression/Classification
• Time series forecasting
• Predictive analytics for forecasting economic indicators 
• Machine learning algorithms for credit scoring and risk management 
• Big Data on economic policy-making
• Data Science in consumer behaviour and market trends
• Data science in international trade and finance
• Macroeconomics and microeconomics
• Behavioural economics and decision-making
• Data-driven decision-making in social policy and welfare
• Predictive modelling for social science research
• Computational social science methods and Techniques
• Big Data and its Implications for social science research
• Ethical Considerations in social science data analysis and Usage
• Predictive Modelling in Economics
• Econometrics and Causal Inference
• Behavioural Economics and Decision Making

Important Dates