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