Registration summary
ConferenceICSLDSAI
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
ICSLDSAI conference tracks support global knowledge exchange, innovation, and sustainable development priorities across diverse disciplines.
01 Advancements in Statistical Learning Techniques +
This track focuses on the latest developments in statistical learning methodologies and their applications in data science. Researchers are invited to present innovative approaches that enhance predictive accuracy and model interpretability.
02 Machine Learning Algorithms for Big Data +
This session explores novel machine learning algorithms specifically designed to handle large-scale datasets. Contributions that demonstrate efficiency and scalability in data processing are particularly encouraged.
03 Neural Networks and Deep Learning Innovations +
This track highlights cutting-edge research in neural networks and deep learning architectures. Papers that address challenges in training, optimization, and real-world applications are welcome.
04 Probabilistic Models in Data Science +
This session aims to delve into the role of probabilistic models in understanding complex data structures. Contributions that integrate probabilistic reasoning with machine learning techniques are particularly sought after.
05 Supervised Learning: Techniques and Applications +
This track covers advancements in supervised learning methods and their practical applications across various domains. Researchers are invited to share insights on algorithm performance and case studies.
06 Unsupervised Learning and Clustering Approaches +
This session focuses on unsupervised learning techniques, including clustering and dimensionality reduction. Papers that propose novel algorithms or frameworks for data exploration are encouraged.
07 Predictive Analytics in Business and Industry +
This track examines the application of predictive analytics in business and industrial contexts. Contributions that showcase real-world impact and case studies of predictive modeling are highly valued.
08 Data Mining Techniques for Knowledge Discovery +
This session is dedicated to data mining methodologies that facilitate knowledge discovery from large datasets. Researchers are invited to present innovative techniques and their implications for data-driven decision-making.
09 Ethics and Fairness in AI and Data Science +
This track addresses the ethical considerations and fairness issues arising in AI and data science applications. Contributions that propose frameworks for responsible AI deployment are encouraged.
10 Interdisciplinary Approaches to Statistical Learning +
This session invites research that intersects statistical learning with other disciplines such as biology, economics, and social sciences. Papers that demonstrate interdisciplinary collaboration and insights are welcomed.
11 Emerging Trends in AI and Data Science +
This track explores emerging trends and future directions in AI and data science. Researchers are encouraged to present visionary ideas and innovative research that push the boundaries of current methodologies.
