Track topics include, but are not limited to:

Track 1: Computational Intelligence in Automation, Control, and Intelligent Transportation System

• Intelligent Decision Making and Support
• Adaptive and Optimal Control
• Model-Predictive Control
• Fuzzy Systems and Control
• Expert and Decision Support Systems
• System Identification and Learning
• Fault Detection and Diagnosis
• Complex System Modelling
• Fuzzy Neural Systems and Control
• Hybrid Intelligent Control
• Advanced transportation information, communication and management systems
• Object recognitions such as pedestrian detection, traffic sign detection and recognition
• Multimodal intelligent transport systems and services
• Vehicle communications and connectivity
• Personalized driver and traveller support systems
• Simulation and forecasting models
• Driver assistance and automation systems
• Driver state detection and monitoring

Track 2: Computational Intelligence on Big Data, Internet of Things, and Smart Cities

• Efficient algorithms on reading, processing and analysis of big data
• Integration of multi-modal, multi-fidelity, and structured and unstructured big data
• Extracting and understanding from distributed, diverse and large-scale data resources
• Visualisation of big data and visual data analytics
• Human-computer interaction and collaboration in big data
• Classification, Clustering, Regression
• Feature learning and feature engineering
• Data mining from nonstationary and drifting environments
• Novel Architecture and Protocols of AI Integrated with IoT
• Security, Privacy, Access Control, and Trust Frameworks of IoT
• Resource Management Techniques of Using AI for IoT
• Control Schemes in IoT
• Smart Data Storage in IoT

Track 3: Computational Intelligence on Wireless Communication Systems and Cyber Security

• Machine Learning for Networks
• V2X Communications
• Unmanned Aerial Vehicles
• Wireless Sensor Networks
• Low Power Wireless Area Networks
• Network Virtualization
• Quality of Service (QoS)
• Resources Management
• Embedded systems
• Software Defined Networks
• Blockchains
• Waveforms and Radio Access Technologies
• Software Defined Radio
• Visible Light Communication (VLC)
• Radio Interference Management
• Radio Access Networks
• Intrusion/malware detection, prediction, classification, and response
• Sensor network security, web security, wireless and 4G, 5G media security
• Self-awareness, auto-defensiveness, self-reconfiguration, and self-healing networking paradigm
• Modelling adversarial behaviour for insider and outsider threat detection
• Cloud and virtualization security
• Block-chain security

Track 4: Computational Intelligence on Human/Brain-Computer Interfaces, and Image and Pattern Recognition

• Signal processing for Brain-Computer Interface (BCI)
• BCI Feature Extraction, Pattern Recognition, and Multiple modalities for BCI
• Invasive and non-invasive BCIs
• Online and offline BCI applications
• Advances on Human-Computer Interfaces
• Feature ranking and weighting
• Feature selection, extraction, construction, and reduction
• Feature analysis on high-dimensional and large-scale data
• Evolutionary computation for feature analysis
• Neural networks for feature analysis
• Fuzzy logic for feature analysis
• Hybrid evolutionary computation and machine learning
• Information theory, statistics, mathematical modelling, etc., for feature analysis
• Feature analysis in classification, clustering, regression, image analysis, and other tasks
• Real-world applications of computational intelligence for feature analysis

Computational intelligence is the science that makes use of biologically and linguistically-
motivated computational paradigms in solving a computational problem, one in which traditional
mathematical modelling is not the preferred solution in addressing a complex real-world problem.
The rationale for this is that (i) the given problem involves computational process that is too
complex for mathematical reasoning; (ii) it might contain some uncertainties during the process,
or (iii) by nature, the computational process is a randomly determined one (heuristic). Hence,
nature-inspired computational solutions are adapted. In addition, computational intelligence has
evolved to include neural networks,  fuzzy logic systems , and evolutionary computation, as well as
social reasoning, artificial life, ambient intelligence, deep learning, and the likes. EAI International Conference on Computational Intelligence and Communications (CICom 2021) is
the venue for which advances in this type of solutions are presented and discussed diligently.

Track topics include, but are not limited to:

• Computational Intelligence in Automation, Control, and Intelligent Transportation System
• Computation Intelligence on Big Data, Internet of Things, and Smart Cities
• Computational Intelligence on Wireless Communication Systems and Cyber Security
• Computational Intelligence on Human/Brain-Computer Interfaces, and Image and Pattern Recognition

This event is organized by EAI.

EAI – European Alliance for Innovation is a non-profit organization and a professional community established in cooperation with the European Commission to empower the global research and innovation, and to promote cooperation between European and International ICT communities.

EAI’s vision is to foster excellence in research and innovation on the principles of transparency, objectivity, equality, and openness. Our guiding principle is community cooperation to create better research, provide fair recognition of excellence and transform best ideas into commercial value proposition.

EAI‘s mission is to create an environment that rewards excellence transparently, and builds recognition objectively regardless of age, economic status or country of origin, where no membership fees or closed door committees stand in the way of your research career.

Through these shared values, EAI leads the way toward advancing the world of research and innovation, empowering individuals and institutions for the good of society to fully benefit from the digital revolution.