International Conference on Statistical Learning and Stochastic Methods
(ICSL-SM-26)

31st October 2026 || Coimbatore - India || Hybrid Mode

Proudly Organized by INRI

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Conference Session Tracks

The International Conference on Statistical Learning and Stochastic Methods (ICSL-SM), scheduled to be held on 31st October 2026 in Coimbatore, India, features a diverse range of session tracks covering key research areas, emerging trends and interdisciplinary innovations within the field of Probability Theory,Statistics.

Each track offers researchers, academicians, industry professionals and practitioners a platform to present their work, exchange ideas and explore the advancements shaping the future of the domain. Every track is curated to encourage knowledge sharing, collaboration and meaningful discussion.

All Session Tracks
  • Track 01 – Advancements in Statistical Learning
    This track focuses on the latest methodologies and innovations in statistical learning. Researchers are encouraged to present their findings on new algorithms and techniques that enhance predictive accuracy and model performance. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 02 – Stochastic Methods in Data Science
    This session will explore the application of stochastic methods in various data science contexts. Contributions should highlight the integration of stochastic processes with modern data analytics techniques. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 03 – Probability Theory and Its Applications
    This track aims to discuss foundational and advanced topics in probability theory. Papers should illustrate the relevance of probability in real-world applications across diverse fields. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 04 – Machine Learning Techniques for Predictive Analytics
    This session invites contributions that showcase machine learning techniques specifically designed for predictive analytics. Emphasis will be placed on novel approaches that improve prediction accuracy and efficiency. Aligned SDGs: SDG 4 – Quality Education  |  SDG 8 – Decent Work and Economic Growth
  • Track 05 – Simulation Methods in Statistical Modeling
    This track will delve into the role of simulation methods in enhancing statistical modeling. Participants are encouraged to present case studies that demonstrate the effectiveness of simulation in model validation and inference. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure  |  SDG 11 – Sustainable Cities and Communities
  • Track 06 – Optimization Techniques in Statistics
    This session will focus on optimization methods utilized in statistical analysis and modeling. Contributions should address both theoretical advancements and practical applications of optimization in statistics. Aligned SDGs: SDG 8 – Decent Work and Economic Growth
  • Track 07 – Applied Statistics in Industry
    This track highlights the application of statistical methods in various industrial sectors. Papers should provide insights into how applied statistics can solve real-world problems and improve decision-making processes. Aligned SDGs: SDG 8 – Decent Work and Economic Growth  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 08 – Regression Analysis and Its Innovations
    This session will explore recent developments in regression analysis techniques. Contributions should focus on novel regression models and their applications in different domains. Aligned SDGs: SDG 4 – Quality Education  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 09 – Clustering Techniques in Big Data
    This track will examine clustering methodologies in the context of big data analytics. Researchers are invited to present innovative clustering algorithms and their effectiveness in handling large datasets. Aligned SDGs: SDG 9 – Industry, Innovation and Infrastructure
  • Track 10 – Quantitative Methods for Risk Analysis
    This session will focus on quantitative approaches to risk analysis and management. Papers should discuss methodologies that quantify risk and their implications for decision-making in uncertain environments. Aligned SDGs: SDG 3 – Good Health and Well-being  |  SDG 9 – Industry, Innovation and Infrastructure
  • Track 11 – Algorithms for Statistical Inference
    This track will cover the development and application of algorithms for statistical inference. Contributions should highlight advancements in computational techniques that enhance inference accuracy and efficiency. Aligned SDGs: SDG 4 – Quality Education  |  SDG 11 – Sustainable Cities and Communities
Alignment with the Sustainable Development Goals
Alongside its academic focus, the conference promotes responsible research, ethical practice and knowledge-driven development. Its session tracks collectively contribute to the following United Nations Sustainable Development Goals.
  • SDG 3 SDG 3
    Good Health and Well-being
  • SDG 4 SDG 4
    Quality Education
  • SDG 8 SDG 8
    Decent Work and Economic Growth
  • SDG 9 SDG 9
    Industry, Innovation and Infrastructure
  • SDG 11 SDG 11
    Sustainable Cities and Communities

Need Assistance?

If you need any clarification on the session tracks or support with your submission, please feel free to reach out to us:

Email: [email protected]

Phone: +91 9677007228