Important Dates
Early Bird Registration :18th July 2026
Paper Submission Deadline :23rd July 2026
Last Date of Registration : 2nd August 2026
Date of Conference : 17th - 18th August 2026
Conference Session Tracks
Aligned with
UN Sustainable Development Goals
This conference contributes to global sustainability by aligning its research discussions and academic sessions with key United Nations Sustainable Development Goals.
SDG 4 — Quality Education
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
SDG 12 — Responsible Consumption and Production
SDG 17 — Partnerships for the Goals
Track 01
Advancements in Predictive Analytics
This track focuses on the latest methodologies and applications of predictive analytics in big data environments. Researchers are encouraged to present novel approaches that enhance prediction accuracy and efficiency.
Track 02
Data Preprocessing Techniques for Big Data
This session will explore innovative data preprocessing methods essential for effective big data analysis. Topics may include data cleaning, normalization, and transformation techniques that improve model performance.
Track 03
Feature Selection and Dimensionality Reduction
This track emphasizes the importance of feature selection and dimensionality reduction in machine learning. Participants will discuss algorithms and strategies that optimize model training and enhance interpretability.
Track 04
Large-Scale Data Processing Frameworks
This session examines frameworks such as Hadoop and Spark that facilitate large-scale data processing. Contributions should highlight performance improvements and case studies demonstrating real-world applications.
Track 05
Distributed Computing for Machine Learning
This track investigates the role of distributed computing in accelerating machine learning tasks. Researchers are invited to present solutions that leverage distributed systems for enhanced scalability and efficiency.
Track 06
Streaming Analytics and Real-Time Processing
This session will focus on techniques for real-time analytics and streaming data processing. Presentations should address challenges and solutions in handling continuous data streams effectively.
Track 07
Clustering Techniques in Big Data
This track explores advanced clustering techniques tailored for big data analytics. Submissions should showcase innovative algorithms and their applications in various domains.
Track 08
Classification Models and Techniques
This session will delve into the development and evaluation of classification models in machine learning. Participants are encouraged to share insights on model selection, training strategies, and performance metrics.
Track 09
Regression Models in Predictive Analytics
This track focuses on the application of regression models in predictive analytics. Contributions should highlight novel approaches to regression analysis and their implications for big data.
Track 10
Data Visualization for Enhanced Insights
This session emphasizes the significance of data visualization in interpreting big data analytics results. Researchers are invited to present techniques that improve data representation and user engagement.
Track 11
Anomaly Detection in Big Data Environments
This track addresses the challenges and methodologies associated with anomaly detection in large datasets. Presentations should focus on innovative techniques that enhance detection accuracy and reduce false positives.