CAIDA 2021 invites submissions of research papers on topics including, but not limited to:
- Machine learning and computational intelligence
- Data modeling and analysis
- Predictive Analytics
- Image Analysis and Processing
- Biometrics and Pattern Recognition
- Machine Learning and Deep Learning
- Big Data, cloud computing and data-intensive systems
- Robotics & IoT Applications
- Smart cities & infrastructure
- Data Visualization
- Virtual Reality/Augmented Reality
- Cybersecurity & AI
- Digital Technologies
- Data Science application in E-commerce and E-governance
- Human-Computer Interaction
- Emerging Artificial Intelligence Applications in Education
- Intelligent Tutoring Systems (ITS)
- Natural Language Processing
- Games and Emerging Technology
- Knowledge representation and symbolic computing
- Cross-disciplinary knowledge management
- Integration of logical reasoning and computer algebra
- Computer vision and computer-aided geometric design
- Intelligent user interfaces for computing systems
- Emerging fields of computational AI such as biocomputing and quantum computing
- Web intelligence
TRACKS
Track 1: Artificial Intelligence & IoT: Current Applications & Future Challenges
Track 2: Big Data Analytics, Data Visualization & Forecasting
Track 3: Artificial Intelligence & Data Analytics applications for COVID-19
Track 4: Multidisciplinary Application of AI & Data Analytics in smart Healthcare; Renewable Energy; IoT, Cybersecurity; Robotics; Smart Technologies; Digital Applications; Education; Smart Agriculture; Business, etc.
Track 1: Artificial Intelligence & IoT: Current Applications & Future Challenges
Machine Learning and Computational Intelligence
Image Analysis and Processing
Biometrics and Pattern Recognition
Machine Learning and Deep Learning
Big Data, Cloud Computing and Data-intensive systems
Virtual /Augmented Reality
Human-Computer Interaction
Natural Language Processing
Games and Emerging Technology
Image/Video Processing
Intrusion Detection
Knowledge representation and Symbolic computing
Cross-disciplinary knowledge management
Integration of logical reasoning and computer algebra
Computer vision and computer-aided geometric design
Intelligent user interfaces for computing systems
Emerging fields of computational AI such as biocomputing and quantum computing
Track 2: Big Data Analytics, Data Visualization & Forecasting
Data Modeling and Analysis
Predictive Analytics
Data Visualization
Tools, frameworks and mechanisms for data analytics
Advanced data analytics topics in Deep/Machine learning
Specific Machine Learning approaches and Data Processing
Sentiment/opinion analysis
Big Data Modeling and Prediction
Web and Social Text mining
Real-World Applications and Case studies of Data Science
Challenges in Data Science and Advanced Analytics
Track 3: Artificial Intelligence & Data Analytics applications for and beyond COVID-19
Global Best Practices in Controlling the COVID-19 Pandemic
AI applications to detect, predict and cure COVID-19
Use of Data Analytics to analyze and predict COVID-19 trends
Epidemiological Forecasting Tools for COVID-19
COVID-19 AI & Machine Learning Challenges
Challenges & Solutions Responding to COVID-19
AI and data analytics application case studies for COVID-19
Track 4: Multidisciplinary Application of AI, IoT & Data Analytics
Artificial Intelligence, IoT & Data Applications in Healthcare
Telemedicine and e-Health / M-Health
Application of Management Technology in Health care
Healthcare Support System
Biomedical imaging, image processing & visualization
Biomedical devices, sensors, and artificial organs
Nanotechnology for biomedical application
Computer-aided and automatic diagnosis
Health monitoring systems
Bio-signal processing and analysis
Biometric and bio-measurement
Artificial Intelligence, IoT & Data Applications in Renewable Energy
An Intelligent Command and control systems for Renewable Energy
Intelligent and Renewable energy for IT equipment
Intelligent and Green technology
Modelling Hydrogen energy storage
Smart Energy efficiency, Smart Grid
Artificial intelligence and machine learning studies for sustainable energies and applications
Computational methods for sustainable energies
Artificial Intelligence, IoT & Data Applications in Agriculture
Data analytics of Socio-Economic dimensions for Sustainable Agriculture & Aquaculture
Smart systems for Plant productivity
Modeling Tools for Agriculture
Artificial Intelligence & Data Applications in Business
Digital economy
Forensic Accounting
Smart Auditing
Financial Reporting
Data Science application in E-commerce and E-governance
Deep Learning in Finance
Digital Marketing
E-Commerce
Artificial Intelligence & Data Applications in Education
Intelligent Tutoring Systems (ITS)
Cognitive models of problem-solving
Cognitive tools for learning
Computer-assisted language learning
Computer-supported collaborative learning
Distributed learning environments
Educational robotics
Embedded training systems
Empirical studies to inform the design of learning environments
Programming learning environment