Important Dates
Early Bird Registration :27th August 2026
Paper Submission Deadline :1st September 2026
Last Date of Registration : 11th September 2026
Date of Conference : 26th - 27th September 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 8 — Decent Work and Economic Growth
SDG 9 — Industry, Innovation and Infrastructure
SDG 11 — Sustainable Cities and Communities
Track 01
Innovations in Bayesian Statistics
This track focuses on the latest advancements in Bayesian methodologies and their applications in various fields. Researchers are encouraged to present novel approaches to Bayesian inference, model selection, and computational techniques.
Track 02
Statistical Inference in High Dimensions
This session will explore statistical inference methods tailored for high-dimensional data settings. Topics may include variable selection, dimensionality reduction, and the challenges of overfitting in complex models.
Track 03
Random Processes and Their Applications
This track aims to delve into the theory and applications of random processes across different domains. Contributions may include stochastic modeling, time series analysis, and applications in finance and engineering.
Track 04
Computational Statistics and Simulation Techniques
This session will highlight innovative computational techniques and simulation methods used in statistical analysis. Participants are invited to share advancements in Monte Carlo methods, bootstrapping, and other resampling techniques.
Track 05
Machine Learning and Statistical Methods
This track will bridge the gap between traditional statistical methods and modern machine learning techniques. Presentations may focus on the integration of statistical theory with machine learning algorithms for improved predictive performance.
Track 06
Data Science and Predictive Analytics
This session will cover the intersection of data science and statistical methodologies for predictive analytics. Topics of interest include data-driven decision-making, model evaluation, and the role of big data in statistical inference.
Track 07
Risk Analysis and Quantitative Methods
This track will focus on the application of quantitative methods in risk analysis across various sectors. Researchers are invited to discuss methodologies for risk assessment, management, and mitigation using statistical tools.
Track 08
Forecasting Techniques in Statistics
This session will explore advanced forecasting methods and their statistical underpinnings. Contributions may include time series forecasting, trend analysis, and the evaluation of forecasting accuracy.
Track 09
Optimization in Statistical Modeling
This track will examine optimization techniques used in the development and refinement of statistical models. Topics may include parameter estimation, model fitting, and the use of optimization algorithms in statistical inference.
Track 10
Algorithms in Statistical Analysis
This session will focus on the development and application of algorithms in statistical analysis. Participants are encouraged to present new algorithms that enhance computational efficiency and accuracy in statistical modeling.
Track 11
Applied Mathematics in Probability Theory
This track will explore the role of applied mathematics in advancing probability theory. Contributions may include theoretical developments, applications in real-world problems, and interdisciplinary approaches to probability.