Conference Information
ICICM 2023: International Conference on Information Communication and Management
Submission Date:
Notification Date:
Conference Date:
Cairo, Egypt
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Call For Papers
Papers describing original work are invited in any of the areas listed below. Acceptance will be based on quality, relevance and originality. Both full research reports and work-in-progress reports are welcome. There will be both oral and poster sessions. The scope of ICICM2023 covers the below topics, but not limited.

Track-1: AI in Digital Marcomm Management

1. AI & Analytics in Marketing Communications
Topics include, but are not limited to, the following:
● Artificial intelligence (AI) in strategic marketing communications decision-making
● Artificial intelligence in advertising
● The possibilities for integrating online and offline communications in the future.
● Mixing human and AI-generated profiles in communications trustworthiness
● The impact of AI on Language, content, and style
● Analytics and insights that can drive marketing communications decisions and channels and tools.
● Data privacy concerns and regulatory responses
● AI in planning, scheduling, and optimizing communications.
● Cross-channel attribution analytics

2. Artificial Intelligence Mediated Communications (AI-MC)

Topics include, but are not limited to, the following:
● The impact on AI on communication education and workforce training
● AI and the future of work in communications
● AI and creativity in IMC
● Can AI be used to block communications (e.g., AI enhanced Ad Blockers)?
● Generative AI and content
● Fake news and deep-fake challenges and detection

3. The Consumer Behavior and AI-enhanced Digital Communications

Topics include, but are not limited to, the following:
● The impact of, AI, immersive technologies, AR, and VR on digital consumers' journey and decision making
● The ethical implications of AI use in communications
● AI-enhanced communication in the VUCA world, and during times of crises
● The potential role of AI to influence public opinion and mood.
● Response to hyper-personalization
● The consequences of User-Generated Content and crowdsourcing of information
● The influence of AI enhanced digital communication on lifestyles, culture, opinions, and quality of life.
Track-2: AI & Communication Technologies

1. Machine Learning (ML) based communications and networking

Topics include, but are not limited to, the following:
● Next-generation networking systems
● Semantic communications
● Drone communications
● Reconfigurable Intelligent Surfaces (RIS)
● Satellite communication systems
● Terahertz communications
● Public Safety Communication systems
● Open Radio Access Networks (O-RAN)
● Age of Information
● Integrated sensing and communications
● Smart Grid communications
● Heterogeneous networks

2. Internet of everything and pervasive computing

Topics include, but are not limited to, the following:
● IoT networking and computing architectures
● Edge, fog, and cloud computing
● AI and machine learning for IoT
● Embedded and energy-harvesting systems
● Low power wide area networks (LPWAN) for IoT
● Implanted and wearable computing
● Mobile data science & analysis
● Mobile health
● Novel applications of wireless signals
● Mobile systems and applications
● Practical quantum applications and systems (quantum sensing, quantum programming, quantum machine learning, etc.)
● Sensing with radio, light, sound, and acoustics
● IoT applications in: smart factories, smart workspace, smart agriculture, education, health, transportation, entertainment, sports, …
● Digital Twins
● IoT and the Metaverse
● Ubiquitous computing and mobile human-computer interaction
● Underwater networking and sensing
● Localization and tracking
● Middleware systems and services
● Data engineering for pervasive computing
● Activity and emotion recognition
● Smart vehicles and drones
● Disaster sensing and management
● Participatory and social sensing
● Device-free sensing
● Social Internet of Things

3. Big Data Analytics and Applied Machine Learning (AML)

Topics include, but are not limited to, the following:
● Time Series Analysis and Forecasting
● Social Network Analysis and Mining
● Machine Learning Applications in the fields of fraud detection and cybersecurity
● Recommender Systems and Personalization Algorithms
● Explainable AI and model interpretability
● Data Visualization and Storytelling
● Federated Learning
● Stream Processing and Event-driven analytical methods
● Real-time Big Data Analytics
● Reinforcement Learning for Decision Support Systems
● Health Analytics and Machine Learning applications in the medical domain
● Transfer Learning and Model Reuse
● Emerging trends and challenges in Machine Learning and Big Data Analytics
Last updated by Dou Sun in 2023-09-14
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