Registration summary
ConferenceICCDA
ModeStandard / Physical
ParticipationListener
Registration fee$175.00
Bank charges (5.8%)$10.15
Total payable$185.15
Includes all bank processing charges — the amount above is exactly what will be charged.
Benefits of Registering as Listener
Access to Conference Sessions
Networking Opportunities
Certificate of Participation
Invitation Letter Support
Conference Kit / Materials
Access to Keynote Sessions
• Conference Session Tracks •
SDG-Aligned Research Themes
ICCDA conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advanced Machine Learning Techniques +
This track focuses on the latest advancements in machine learning theories, models, and systems. It aims to explore innovative approaches to enhance learning efficiency and effectiveness across various applications.
02 Data Pre-processing and Dimensionality Reduction +
This session emphasizes the importance of data pre-processing techniques, including sampling and reduction methods. It will also cover dimensionality reduction strategies that facilitate more efficient data analysis.
03 High Performance Computing for Data Analytics +
This track investigates the role of high-performance computing in enhancing data analytics capabilities. Discussions will include architectures and processes that optimize computational resources for large-scale data analysis.
04 Knowledge Discovery and Insight Learning +
This session is dedicated to theories and models related to knowledge discovery and latent insight learning. It will explore methodologies that extract valuable information from complex datasets.
05 Big Data Visualization and Modeling +
This track addresses the challenges and techniques in visualizing and modeling big data. Participants will discuss innovative visualization methods that aid in understanding and interpreting large datasets.
06 Cloud Computing and Service Data Analysis +
This session focuses on the integration of cloud computing technologies in data analysis. It will explore how cloud services can enhance data management and processing capabilities.
07 Mining Multi-source and Mixed-source Information +
This track delves into methodologies for mining information from multiple and mixed data sources. It aims to highlight techniques that effectively integrate heterogeneous data for comprehensive analysis.
08 Computational Science in Engineering Applications +
This session explores the application of computational science principles in various engineering domains. It will highlight case studies and methodologies that leverage computational techniques for engineering solutions.
09 Web and Social Network Mining +
This track focuses on mining techniques applied to web and social network data. Discussions will include methods for extracting insights from social interactions and online behaviors.
10 Personalization Analytics and Learning +
This session examines the theories and models behind personalization analytics. It will explore how data-driven approaches can enhance user experiences through tailored recommendations.
11 Graph Mining and Network Analysis +
This track investigates the methodologies for relation, coupling, and graph mining. It aims to explore techniques for analyzing network structures and community dynamics within complex datasets.
