ICDDS’23 invites submissions discussing original research contributions on all aspects of data science, management of data, artificial intelligence, machine/deep learning and their applications focused on theoretical formulations, experimentations, benchmarking, scalability, trustworthiness of algorithms, novel algorithms and computing, etc. Authors can submit papers maximum of 6 pages including references.Accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. For more details check Author's Guidelines.

The topics of interests include, but are not limited to:

• Probabilistic Inference (Bayesian methods, graphical models, Monte Carlo methods, etc.)
• Online learning
• Generative models
• Representation learning for computer vision
• Data privacy and new system design
• Big data systems
• New Computational Models for Big Data
• New Data Standards
• Semantic-based Data Mining and Data Pre-processing
• Learning Theory (bandits, game theory, statistical learning theory, etc.)
• ML and Deep learning
• Web analytics
• Data mining
• Optimization
• Ethics in artificial intelligence
• Social computing and analytics
• Algorithms and systems for database
• ML for embedded platforms
• Recommender systems
• Multimedia processing
• Analytics method and systems
• Text analytics and NLP
• Time-series analysis
• Information retrieval
• Semantic-based Data Mining and Data Pre-processing